rolling view · 11 complete · 7 partial · 0 valid negative / 25 lanes

Antfly Circus — Latest

The newest reviewed result available for each Antfly benchmark lane. Sections may use different Antfly releases or main commits; every evidence block names its exact Antfly subject.

Reading contract

Latest selects the newest reviewed outcome available for each lane. Antfly versions, machines, dates, and protocols may differ; every evidence block names its exact subject.

3 of 3 lanes measured

VectorDBBench

Qualified vector search quality, throughput, serial latency, serving demand, and database volume across operating points.

vector-vdbbench-50k

complete

50K

Antfly main-09b78df97, stripped ReleaseFast, passed three fresh 50K lifecycles at a 30-client ceiling with zero request errors: recall 0.963 and mean peak throughput 834.0 QPS.

Methodology scope · protocol · interpretation

Standard vector publication protocol

Each of three fresh Linux ARM64 lifecycles builds one index, selects its search-time setting using only 200 deterministic calibration queries, and measures the disjoint 800-query publication holdout without rebuilding. The complete publication sweep uses 1, 5, 10, 20, and 30 clients for 30 seconds per point, plus a serial pass. Every lifecycle must complete the declared sweep with zero request errors. Results do not establish capacity above 30 clients.

Throughput and latency are arithmetic means across the three lifecycles; retained per-concurrency observations include trial values and ranges. Database-service memory demand is sampled cgroup anon + shmem from before indexing through publication, excluding the benchmark client. Final database volume is checksum-verified post-stop allocated bytes across the complete declared volume, with three-trial mean and range.

Historical peer observations retain their original versions and dates. They are reference measurements, not fresh matched comparisons; no peer database was rerun.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: vector-vdbbench-50k
Domain: vector
Source: https://github.com/antflydb/VectorDBBench
Upstream: https://github.com/zilliztech/VectorDBBench
Known Antfly versions: v0.1.3, v0.2.*
Expected duration: 480 min
Enabled: yes

Benchmark parameters

{"concurrency_duration_seconds":30,"concurrency_schedule":[1,5,10,20,30],"execution_environment":{"container_runtime":"podman podman version 6.1.1","controller_platform":"darwin-arm64","processor":"Apple M4 Max","service_platform":"linux-arm64","vm_cpus":10,"vm_memory_bytes":29347610624,"vm_memory_gib":27.3},"lifecycle_search_values":[0.45,0.45,0.45],"query_count":800,"query_partition_sha256":"7be5c5f24dfa31b66c5dfc3280c8f1bc5c1c8db3a35046a1a1ab9d50a0d232f7","search_parameter":"search_effort"}

Trial variation

[{"engine":"Antfly","ranges":{"demand_working_set":{"maximum":1444.2,"mean":1348.8,"minimum":1290.7,"unit":"MB"},"final_database_volume":{"maximum":368.443392,"mean":368.050176,"minimum":367.521792,"unit":"MB"},"p99_at_30_concurrent":{"maximum":88.2,"mean":86.1,"minimum":84.3,"unit":"ms"}},"workload":"1536d-50K"},{"engine":"Chroma","ranges":{"demand_working_set":{"maximum":466.7,"mean":463.3,"minimum":460.9,"unit":"MB"},"final_database_volume":{"maximum":332.488704,"mean":332.485973,"minimum":332.480512,"unit":"MB"},"p99_at_30_concurrent":{"maximum":179,"mean":177.6,"minimum":175.3,"unit":"ms"}},"workload":"1536d-50K"},{"engine":"Elasticsearch","ranges":{"demand_working_set":{"maximum":1952.7,"mean":1941,"minimum":1934.8,"unit":"MB"},"final_database_volume":{"maximum":312.082432,"mean":312.067413,"minimum":312.049664,"unit":"MB"},"p99_at_30_concurrent":{"maximum":15.1,"mean":14.467,"minimum":14,"unit":"ms"}},"workload":"1536d-50K"},{"engine":"Milvus 2.6.22","ranges":{"demand_working_set":{"maximum":2766.6,"mean":2666.2,"minimum":2563.6,"unit":"MB"},"final_database_volume":{"maximum":2393.47712,"mean":2393.459371,"minimum":2393.432064,"unit":"MB"},"p99_at_30_concurrent":{"maximum":11.4,"mean":11.233,"minimum":11.1,"unit":"ms"}},"workload":"1536d-50K"},{"engine":"pgvector","ranges":{"demand_working_set":{"maximum":2303.8,"mean":2303.7,"minimum":2303.7,"unit":"MB"},"final_database_volume":{"maximum":1523.970048,"mean":1523.967317,"minimum":1523.965952,"unit":"MB"},"p99_at_30_concurrent":{"maximum":33.1,"mean":32.033,"minimum":31.4,"unit":"ms"}},"workload":"1536d-50K"},{"engine":"Weaviate","ranges":{"demand_working_set":{"maximum":977.9,"mean":953.8,"minimum":936.6,"unit":"MB"},"final_database_volume":{"maximum":391.55712,"mean":391.514795,"minimum":391.491584,"unit":"MB"},"p99_at_30_concurrent":{"maximum":89.6,"mean":86.967,"minimum":85.3,"unit":"ms"}},"workload":"1536d-50K"},{"engine":"Milvus 3.0.0","ranges":{"demand_working_set":{"maximum":2949.6,"mean":2819,"minimum":2719.7,"unit":"MB"},"final_database_volume":{"maximum":2489.167872,"mean":2489.156949,"minimum":2489.143296,"unit":"MB"},"p99_at_30_concurrent":{"maximum":12,"mean":11.667,"minimum":11.4,"unit":"ms"}},"workload":"1536d-50K"}]

Peer versions

Chroma1.5.9
Elasticsearch9.5.2
Milvus 2.6.222.6.22
pgvector0.8.6 (PostgreSQL 16)
Weaviate1.39.2
Milvus 3.0.03.0.0

Evidence digests

Receipt: 488df681970e7beba9a2fb9d6b81d7d0a690a82c041568f5ff12aa4bb559d7bd
Aggregate: 0349cf53351b72af9d3e6b8b1296b2a68987060cf4e186f71d105573eeafd065
Provenance: 0349cf53351b72af9d3e6b8b1296b2a68987060cf4e186f71d105573eeafd065
Harness commit: 82c699bb7a687b65efc691ec329368494ce8499e

Peer cohort evidence · 1536d-50K

Completed: 28 Aug 2026 · 14:56 UTC
Fresh lifecycles: 18
Peer variants: 6
Receipt: 782e8e470765fae9914945e67c9da3f3e82a1b38571ebe6e5940228a8248601c
Aggregate: 0eb49aba01e15e065ec68b1667beb2c41a580cde5dab2cb928b6f8c01c16daf4
Provenance: 700d49bf35039da97e9b5366d4a4e6ec4c417fdfdb5fd720b980349a538d68c3

Selected measurement

Completed: 7 Oct 2026 · 01:46 UTC
Antfly: main-09b78df97 · 6 October 2026 · 00:55 UTC
Runtime: 1h 34m
Platform: linux · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Peer cohort · 1536d-50K

Completed: 28 Aug 2026 · 14:56 UTC
Variants: 6 independently executed peers
Lifecycles: 18 fresh
Compatibility: Historical reference · not a matched runtime

Peak throughput

Antfly main-09b78df97 (09b78df9, ReleaseFast/stripped) · linux-arm64 · 1536d-50K · three fresh lifecycles · 1/5/10/20/30 clients · 30 s/point · partition seed antfly-circus-vdbbench-v1 · Higher is better · Apple M4 Max · podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Serial query p95

Antfly main-09b78df97 (09b78df9, ReleaseFast/stripped) · linux-arm64 · 1536d-50K · three fresh lifecycles · 1/5/10/20/30 clients · 30 s/point · partition seed antfly-circus-vdbbench-v1 · Lower is better · Apple M4 Max · podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Demand working set

Antfly main-09b78df97 (09b78df9, ReleaseFast/stripped) · linux-arm64 · 1536d-50K · three fresh lifecycles · 1/5/10/20/30 clients · 30 s/point · partition seed antfly-circus-vdbbench-v1 · Lower is better · Apple M4 Max · podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Final database volume

Antfly main-09b78df97 (09b78df9, ReleaseFast/stripped) · linux-arm64 · 1536d-50K · three fresh lifecycles · 1/5/10/20/30 clients · 30 s/point · partition seed antfly-circus-vdbbench-v1 · Lower is better · Apple M4 Max · podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Performance, quality, and resource evidence

Antfly main-09b78df97 · 09b78df9

Engine	Workload	Recall	nDCG	Peak QPS queries/s	p95 ms	Demand working set MB	Cache-inclusive peak MB	Final database volume MB	Trials
Antfly	1536d-50K	0.9630	0.9670	834.0	8.867	1,348.8 MB	1,785.2 MB	368.1 MB	3
Chroma	1536d-50K	0.9870	0.9890	180.9	8.067	463.3 MB	812.9 MB	332.5 MB	3
Elasticsearch	1536d-50K	0.9560	0.9640	4,434.6	2.033	1,941.0 MB	4,385.1 MB	312.1 MB	3
Milvus 2.6.22	1536d-50K	0.9630	0.9700	5,293.1	1.600	2,666.2 MB	5,426.1 MB	2,393.5 MB	3
pgvector	1536d-50K	0.9690	0.9750	2,721.0	4.167	2,303.7 MB	3,533.5 MB	1,524.0 MB	3
Weaviate	1536d-50K	0.9550	0.9630	1,008.8	6.300	953.8 MB	1,511.3 MB	391.5 MB	3
Milvus 3.0.0	1536d-50K	0.9630	0.9700	5,019.7	1.700	2,819.0 MB	5,557.7 MB	2,489.2 MB	3

vector-vdbbench-1m

complete

1M

Antfly main-09b78df97, stripped ReleaseFast, passed three fresh 1M lifecycles at a 30-client ceiling with zero request errors: recall 0.963 and mean peak throughput 591.9 QPS.

Methodology scope · protocol · interpretation

Standard vector publication protocol

Historical peer observations retain their original versions and dates. They are reference measurements, not fresh matched comparisons; no peer database was rerun.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: vector-vdbbench-1m
Domain: vector
Source: https://github.com/antflydb/VectorDBBench
Upstream: https://github.com/zilliztech/VectorDBBench
Known Antfly versions: v0.1.3, v0.2.*
Expected duration: 480 min
Enabled: yes

Benchmark parameters

{"concurrency_duration_seconds":30,"concurrency_schedule":[1,5,10,20,30],"execution_environment":{"container_runtime":"podman podman version 6.1.1","controller_platform":"darwin-arm64","processor":"Apple M4 Max","service_platform":"linux-arm64","vm_cpus":10,"vm_memory_bytes":29347610624,"vm_memory_gib":27.3},"lifecycle_search_values":[0.425,0.425,0.425],"query_count":800,"query_partition_sha256":"7be5c5f24dfa31b66c5dfc3280c8f1bc5c1c8db3a35046a1a1ab9d50a0d232f7","search_parameter":"search_effort"}

Trial variation

[{"engine":"Antfly","ranges":{"demand_working_set":{"maximum":4521.2,"mean":4246.7,"minimum":3837.8,"unit":"MB"},"final_database_volume":{"maximum":5937.778688,"mean":5928.665088,"minimum":5918.507008,"unit":"MB"},"p99_at_30_concurrent":{"maximum":144.2,"mean":135.5,"minimum":119.6,"unit":"ms"}},"workload":"768d-1M"},{"engine":"Chroma","ranges":{"demand_working_set":{"maximum":3699.1,"mean":3693.6,"minimum":3688.8,"unit":"MB"},"final_database_volume":{"maximum":3460.194304,"mean":3459.731456,"minimum":3458.838528,"unit":"MB"},"p99_at_30_concurrent":{"maximum":136.1,"mean":135.567,"minimum":134.6,"unit":"ms"}},"workload":"768d-1M"},{"engine":"Elasticsearch","ranges":{"demand_working_set":{"maximum":2135.8,"mean":2095.2,"minimum":2029.8,"unit":"MB"},"final_database_volume":{"maximum":3148.750848,"mean":3148.500992,"minimum":3148.361728,"unit":"MB"},"p99_at_30_concurrent":{"maximum":21.6,"mean":20.967,"minimum":19.7,"unit":"ms"}},"workload":"768d-1M"},{"engine":"Milvus 2.6.22","ranges":{"demand_working_set":{"maximum":13999.4,"mean":13920.6,"minimum":13837.1,"unit":"MB"},"final_database_volume":{"maximum":25669.378048,"mean":25642.164224,"minimum":25626.836992,"unit":"MB"},"p99_at_30_concurrent":{"maximum":13.7,"mean":13.633,"minimum":13.5,"unit":"ms"}},"workload":"768d-1M"},{"engine":"pgvector","ranges":{"demand_working_set":{"maximum":2318.6,"mean":2317.3,"minimum":2316.6,"unit":"MB"},"final_database_volume":{"maximum":9329.364992,"mean":9329.318571,"minimum":9329.27488,"unit":"MB"},"p99_at_30_concurrent":{"maximum":76.6,"mean":72.867,"minimum":69.9,"unit":"ms"}},"workload":"768d-1M"},{"engine":"Weaviate","ranges":{"demand_working_set":{"maximum":7370.7,"mean":7345.1,"minimum":7331,"unit":"MB"},"final_database_volume":{"maximum":3955.232768,"mean":3947.47904,"minimum":3942.985728,"unit":"MB"},"p99_at_30_concurrent":{"maximum":68.3,"mean":67.2,"minimum":65.7,"unit":"ms"}},"workload":"768d-1M"},{"engine":"Milvus 3.0.0","ranges":{"demand_working_set":{"maximum":13551.8,"mean":13262.6,"minimum":13016.7,"unit":"MB"},"final_database_volume":{"maximum":35112.308736,"mean":33718.551893,"minimum":33003.88864,"unit":"MB"},"p99_at_30_concurrent":{"maximum":14.4,"mean":14.233,"minimum":14.1,"unit":"ms"}},"workload":"768d-1M"}]

Peer versions

Chroma1.5.9
Elasticsearch9.5.2
Milvus 2.6.222.6.22
pgvector0.8.6 (PostgreSQL 16)
Weaviate1.39.2
Milvus 3.0.03.0.0

Evidence digests

Receipt: bee7787ceaa3b737a0b5da4888039e04369d810d0823d376e232d6bc289da5de
Aggregate: 15c0f5c09b43c79611ddbadf40f16e829f99d32c85873b47d336be08ad4c47ab
Provenance: 15c0f5c09b43c79611ddbadf40f16e829f99d32c85873b47d336be08ad4c47ab
Harness commit: 82c699bb7a687b65efc691ec329368494ce8499e

Peer cohort evidence · 768d-1M

Completed: 28 Aug 2026 · 15:20 UTC
Fresh lifecycles: 18
Peer variants: 6
Receipt: 4366569aa9cfe5f7e796c5eadc30a6d2ae610cde650543eb3546ddcb856dfebf
Aggregate: 828e2d97f299926c3bb1f39866db983ef61895793243ec02a569fe955507a197
Provenance: 4af875e079c7c2538ed378027ac14be10294f30a7761e8fe0300f885ea3a1ea4

Selected measurement

Completed: 7 Oct 2026 · 01:46 UTC
Antfly: main-09b78df97 · 6 October 2026 · 00:55 UTC
Runtime: 1h 34m
Platform: linux · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Peer cohort · 768d-1M

Completed: 28 Aug 2026 · 15:20 UTC
Variants: 6 independently executed peers
Lifecycles: 18 fresh
Compatibility: Historical reference · not a matched runtime

Peak throughput

Antfly main-09b78df97 (09b78df9, ReleaseFast/stripped) · linux-arm64 · 768d-1M · three fresh lifecycles · 1/5/10/20/30 clients · 30 s/point · partition seed antfly-circus-vdbbench-v1 · Higher is better · Apple M4 Max · podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Serial query p95

Antfly main-09b78df97 (09b78df9, ReleaseFast/stripped) · linux-arm64 · 768d-1M · three fresh lifecycles · 1/5/10/20/30 clients · 30 s/point · partition seed antfly-circus-vdbbench-v1 · Lower is better · Apple M4 Max · podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Demand working set

Antfly main-09b78df97 (09b78df9, ReleaseFast/stripped) · linux-arm64 · 768d-1M · three fresh lifecycles · 1/5/10/20/30 clients · 30 s/point · partition seed antfly-circus-vdbbench-v1 · Lower is better · Apple M4 Max · podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Final database volume

Antfly main-09b78df97 (09b78df9, ReleaseFast/stripped) · linux-arm64 · 768d-1M · three fresh lifecycles · 1/5/10/20/30 clients · 30 s/point · partition seed antfly-circus-vdbbench-v1 · Lower is better · Apple M4 Max · podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Performance, quality, and resource evidence

Antfly main-09b78df97 · 09b78df9

Engine	Workload	Recall	nDCG	Peak QPS queries/s	p95 ms	Demand working set MB	Cache-inclusive peak MB	Final database volume MB	Trials
Antfly	768d-1M	0.9630	0.9670	591.9	17.800	4,246.7 MB	10,241.9 MB	5,928.7 MB	3
Chroma	768d-1M	0.9560	0.9620	238.7	6.600	3,693.6 MB	7,289.8 MB	3,459.7 MB	3
Elasticsearch	768d-1M	0.9590	0.9610	3,110.8	3.233	2,095.2 MB	11,426.8 MB	3,148.5 MB	3
Milvus 2.6.22	768d-1M	0.9610	0.9660	4,085.9	2.200	13,920.6 MB	21,605.9 MB	25,642.2 MB	3
pgvector	768d-1M	0.9660	0.9700	955.8	10.767	2,317.3 MB	11,974.9 MB	9,329.3 MB	3
Weaviate	768d-1M	0.9560	0.9620	1,300.8	5.700	7,345.1 MB	13,791.8 MB	3,947.5 MB	3
Milvus 3.0.0	768d-1M	0.9610	0.9670	3,898.5	2.367	13,262.6 MB	21,631.0 MB	33,718.6 MB	3

iii

vector-vdbbench-scale

complete

Scale

Antfly main-09b78df97, stripped ReleaseFast, completed all 24 fresh lifecycles across twelve corpus sizes from 20K to 3M with zero request errors. At 3M, peak throughput averaged 222 QPS across a 114–330 QPS range; service demand averaged 9.21 GB and final allocated volume 29.97 GB. This is a two-lifecycle scale diagnostic, separate from three-lifecycle honed publication.

Methodology scope · protocol · interpretation

Vector scale diagnostic: retained methodology

The complete cohort contains Fast 20K,40K,60K,80K,100K and Big 200K,400K,600K,800K,1M,2M,3M: 12 sizes, two fresh lifecycles each (24 cells), 1/5/10/20/30 clients for 30 seconds each (120 concurrency windows). Trial 1 traverses all sizes ascending; trial 2 descends. This is descriptive two-lifecycle evidence, not the three-lifecycle honed publication cohort.

All sizes use deterministic zero-copy prefixes of the first three pinned Cohere10M training shards, the same 1000 test embeddings, exact cosine top-100 prefix ground truth, dimensions 768, and float32 L2 normalization. Seed antfly-circus-vdbbench-v1 separates 200 calibration and 800 held-out publication queries without overlap. The lowest calibrated search effort reaching recall 0.955 is selected; held-out quality must meet 0.95. Dataset manifests and source checksums are retained in the neutral protocol.

The final cohort uniformly uses persistent-stdin-exec memory collection. Demand measures cgroup-v2 anon+shmem through the full lifecycle, excludes reclaimable file cache, and keeps exact peak bytes, sample counts, coverage boundaries and maximum gaps beside rounded source metrics. Storage retains allocated/apparent byte observations at empty,ready,post-workload,final barriers, service-stop qualification and receipt fingerprints; the selected yardstick is final allocated bytes. Product defaults remain unchanged.

Concurrency latency arrays retain original seconds; aggregate p95/p99 observations convert to milliseconds. Means and ranges are arithmetic across trial 1 then trial 2; percentile means are not pooled percentiles. Full numerical publication metrics, serial calibration candidates and selected settings, index-build components, lifecycle timing, source-cell object/receipt digests and timestamps remain evidence.

Earlier one-shot captures and previous/historical comparisons are supplementary only and never pooled into selected metrics. Attempt 2 retains eleven qualified trial-1 cells and an unqualified 3M query observation: its three failed memory samples and 92.91-second maximum gap forbid qualifying the observed memory peak. The slot exhausted two attempts; first-attempt detailed files were overwritten by the previous retry policy and are not synthesized. Collector recovery and independent final verification are attached. Fixed ascending client sweeps confound client count with elapsed time. Cross-run binary/build/environment/fixture/load differences prohibit causal product speedup claims.

Raw logs, memory timelines, query text, corpora and binaries remain Circus-side; this package retains portable artifact names and verified checksums, not fabricated public uploads.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: vector-vdbbench-scale
Domain: vector/scale
Source: https://github.com/antflydb/VectorDBBench
Upstream: https://github.com/zilliztech/VectorDBBench
Known Antfly versions: v0.2.*
Enabled: yes

Benchmark parameters

{"calibration_qualification_floor":0.955,"calibration_queries":200,"client_import_mode":"selected","concurrency_schedule":[1,5,10,20,30],"dataset_generator":"circus-cohere-10m-scale-prefix-v1","dataset_manifests":[{"artifact_identity":{"bytes":1351,"files_count":1,"sha256":"519ec730306a19f504b958cdef58ab4ba702c089a3d38ba8c15c310dbad447ef"},"manifest":{"dimensions":768,"generation":{"batch_rows":4096,"normalization":"float32 L2","prefix_order":"ordered source shard rows","tie_break":"score descending then vector ID ascending"},"generator":"circus-cohere-10m-scale-prefix-v1","metric":"cosine","outputs":{"neighbors.parquet":"62200b46789213490b034feafa5a5bada1a01ce20de90236a32bab43b3304c1b","test.parquet":"a3b0416f2e7eb0e932a0f15f75ed25c76d53777cd7e52d74b1b2e62066f46a4c"},"queries":1000,"schema_version":1,"source_relative":"cohere/cohere_large_10m","source_row_range":[0,20000],"source_sha256":{"scalar_labels.parquet":"604613ff5cdb4086c94ff5168538e96c503517efd0489f6b44ed53a229568251","shuffle_train-00-of-10.parquet":"f7bc9a94961d2d45856d6c49e0fa35465ea8919a063c5bc5c06df289eb5f3d3c","shuffle_train-01-of-10.parquet":"4cbeaa1447c91c7a47923f995db5f76d63a979e528845236c7d2fdbb6877fd77","shuffle_train-02-of-10.parquet":"69d23f161942d549c5416c8b74464c193dbd0c4d3c024440e32fa3f7935bb3f5","test.parquet":"a3b0416f2e7eb0e932a0f15f75ed25c76d53777cd7e52d74b1b2e62066f46a4c"},"top_k":100,"training_file_rows":[1000000],"training_files":["cohere/cohere_large_10m/shuffle_train-00-of-10.parquet"],"vectors":20000,"zero_copy_training":true},"manifest_sha256":"39304250117bdaf86b96d999d75f9b9771794955d5718b23f3370959f133c3cf"},{"artifact_identity":{"bytes":1351,"files_count":1,"sha256":"cfec0511b2ebdc992c66ca78494eb77939f1c32c99f7b36fcf20bcebd706d2a9"},"manifest":{"dimensions":768,"generation":{"batch_rows":4096,"normalization":"float32 L2","prefix_order":"ordered source shard rows","tie_break":"score descending then vector ID 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Execution provenance

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Where the time went

One pinned Cohere10M-source fixture supplies nested 768D prefixes at all twelve sizes, with 200 calibration queries and a disjoint 800-query holdout. Each of two fresh lifecycles sweeps 1/5/10/20/30 clients for 30 seconds per point; all use the same frozen binary, default server settings, and persistent cgroup collector. At 1M, 10 to 20 clients adds only 3.1% throughput while p99 more than doubles. Mean peak throughput falls from 797 QPS at 1M to 445 at 2M and 222 at 3M; 3M trial peaks range from 114 to 330 QPS. One 3M/20-client window reached 10.73 seconds p99 despite zero request errors. Fixed-order sweeps confound concurrency with elapsed lifecycle time; the cause of the variation is not isolated, and these observations are not stable-capacity bounds. Adding 50% more vectors from 2M to 3M costs 1.91 times the allocated storage and 2.71 times the build time. Demand is database-service cgroup anon + shmem, excluding the client. Per-trial concurrency observations, earlier-result comparisons, superseded measurements, and capture recovery are retained in Run details. Earlier honed and scale fixtures and the old one-shot collector are not matched with this run; no product speedup is claimed. The failed 3M capture remains unqualified and is not mixed into the clean curve.

Trial variation

Each size retains ordered trials 1 and 2, held-out qualification and selected effort. When captured, concurrency observations report QPS and p95/p99 in milliseconds at every client count; original publication metric latency arrays remain in seconds. These are two-lifecycle diagnostics, not the three-lifecycle honed cohort.

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Attachment SHA-256: d263db27d0cc461b26c1cd739b80951181f5b64fe6c93e4a4b5878a51f63deda

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Superseded scale observations

Superseded diagnostic evidence, not selected headline results. Failed memory captures remain unqualified.

Attachment SHA-256: c431b0f6e3c4f4e3a5d3b87450ecbe33a0981e75499b71dda2b2b2d581b9689c

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Capture recovery

Capture-method recovery evidence; earlier one-shot captures are not mixed into the selected persistent-stdin cohort.

Attachment SHA-256: 696f5f055a96085c29ca709c254e0e024a32e63ea22e5a0bba9edd2a8fdd7ef0

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speedup."],"memory_capture":{"all_captures":[{"demand_mb":1825.8,"failed_samples":0,"max_sample_gap_s":0.296,"samples":2911,"service_containers":["antfly_bench_vdbb_scale_t1_scale-fast-20k"],"trial":1,"vectors":20000},{"demand_mb":1825.4,"failed_samples":0,"max_sample_gap_s":0.244,"samples":2890,"service_containers":["antfly_bench_vdbb_scale_t2_scale-fast-20k"],"trial":2,"vectors":20000},{"demand_mb":2132.5,"failed_samples":0,"max_sample_gap_s":0.256,"samples":2938,"service_containers":["antfly_bench_vdbb_scale_t1_scale-fast-40k"],"trial":1,"vectors":40000},{"demand_mb":1361,"failed_samples":0,"max_sample_gap_s":0.255,"samples":2944,"service_containers":["antfly_bench_vdbb_scale_t2_scale-fast-40k"],"trial":2,"vectors":40000},{"demand_mb":2150.9,"failed_samples":0,"max_sample_gap_s":0.234,"samples":2962,"service_containers":["antfly_bench_vdbb_scale_t1_scale-fast-60k"],"trial":1,"vectors":60000},{"demand_mb":1953.2,"failed_samples":0,"max_sample_gap_s":0.242,"samples":2955,"service_containers":["antfly_bench_vdbb_scale_t2_scale-fast-60k"],"trial":2,"vectors":60000},{"demand_mb":2226.4,"failed_samples":0,"max_sample_gap_s":0.229,"samples":2985,"service_containers":["antfly_bench_vdbb_scale_t1_scale-fast-80k"],"trial":1,"vectors":80000},{"demand_mb":2296.9,"failed_samples":0,"max_sample_gap_s":0.227,"samples":2996,"service_containers":["antfly_bench_vdbb_scale_t2_scale-fast-80k"],"trial":2,"vectors":80000},{"demand_mb":2183,"failed_samples":0,"max_sample_gap_s":0.264,"samples":3019,"service_containers":["antfly_bench_vdbb_scale_t1_scale-fast-100k"],"trial":1,"vectors":100000},{"demand_mb":2275.8,"failed_samples":0,"max_sample_gap_s":0.28,"samples":3027,"service_containers":["antfly_bench_vdbb_scale_t2_scale-fast-100k"],"trial":2,"vectors":100000},{"demand_mb":2676.4,"failed_samples":0,"max_sample_gap_s":0.44,"samples":3182,"service_containers":["antfly_bench_vdbb_scale_t1_scale-big-200k"],"trial":1,"vectors":200000},{"demand_mb":2107.4,"failed_samples":0,"max_sample_gap_s":0.229,"samples":3192,"service_containers":["antfly_bench_vdbb_scale_t2_scale-big-200k"],"trial":2,"vectors":200000},{"demand_mb":2829.8,"failed_samples":0,"max_sample_gap_s":0.23,"samples":3567,"service_containers":["antfly_bench_vdbb_scale_t1_scale-big-400k"],"trial":1,"vectors":400000},{"demand_mb":2412.9,"failed_samples":0,"max_sample_gap_s":0.249,"samples":3538,"service_containers":["antfly_bench_vdbb_scale_t2_scale-big-400k"],"trial":2,"vectors":400000},{"demand_mb":2870.5,"failed_samples":0,"max_sample_gap_s":0.322,"samples":4023,"service_containers":["antfly_bench_vdbb_scale_t1_scale-big-600k"],"trial":1,"vectors":600000},{"demand_mb":2820,"failed_samples":0,"max_sample_gap_s":0.226,"samples":4078,"service_containers":["antfly_bench_vdbb_scale_t2_scale-big-600k"],"trial":2,"vectors":600000},{"demand_mb":3464.2,"failed_samples":0,"max_sample_gap_s":0.238,"samples":4474,"service_containers":["antfly_bench_vdbb_scale_t1_scale-big-800k"],"trial":1,"vectors":800000},{"demand_mb":3938.3,"failed_samples":0,"max_sample_gap_s":0.341,"samples":4630,"service_containers":["antfly_bench_vdbb_scale_t2_scale-big-800k"],"trial":2,"vectors":800000},{"demand_mb":3842.2,"failed_samples":0,"max_sample_gap_s":0.269,"samples":4956,"service_containers":["antfly_bench_vdbb_scale_t1_scale-big-1m"],"trial":1,"vectors":1000000},{"demand_mb":3981.5,"failed_samples":0,"max_sample_gap_s":0.28,"samples":5135,"service_containers":["antfly_bench_vdbb_scale_t2_scale-big-1m"],"trial":2,"vectors":1000000},{"demand_mb":6241,"failed_samples":0,"max_sample_gap_s":0.235,"samples":8527,"service_containers":["antfly_bench_vdbb_scale_t1_scale-big-2m"],"trial":1,"vectors":2000000},{"demand_mb":6816.4,"failed_samples":0,"max_sample_gap_s":0.545,"samples":9110,"service_containers":["antfly_bench_vdbb_scale_t2_scale-big-2m"],"trial":2,"vectors":2000000},{"demand_mb":9227.4,"failed_samples":0,"max_sample_gap_s":0.359,"samples":30180,"service_containers":["antfly_bench_vdbb_scale_t1_scale-big-3m"],"trial":1,"vectors":3000000},{"demand_mb":9190.7,"failed_samples":0,"max_sample_gap_s":0.389,"samples":24226,"service_containers":["antfly_bench_vdbb_scale_t2_scale-big-3m"],"trial":2,"vectors":3000000}],"failed_samples":0,"large_captures":[{"demand_mb":6241,"failed_samples":0,"max_sample_gap_s":0.235,"samples":8527,"service_containers":["antfly_bench_vdbb_scale_t1_scale-big-2m"],"trial":1,"vectors":2000000},{"demand_mb":6816.4,"failed_samples":0,"max_sample_gap_s":0.545,"samples":9110,"service_containers":["antfly_bench_vdbb_scale_t2_scale-big-2m"],"trial":2,"vectors":2000000},{"demand_mb":9227.4,"failed_samples":0,"max_sample_gap_s":0.359,"samples":30180,"service_containers":["antfly_bench_vdbb_scale_t1_scale-big-3m"],"trial":1,"vectors":3000000},{"demand_mb":9190.7,"failed_samples":0,"max_sample_gap_s":0.389,"samples":24226,"service_containers":["antfly_bench_vdbb_scale_t2_scale-big-3m"],"trial":2,"vectors":3000000}],"max_sample_gap_s":0.545},"receipt_files_verified":1014,"retention_limit":{"first_attempt_detail_status":"overwritten-by-previous-retry-policy","first_attempt_numerical_metrics_available":false,"retained_detailed_attempt":2,"slot_attempts_exhausted":2,"synthesized_observations":0},"scale_changes":[{"demand_ratio":1.6689545867045004,"from_vectors":1000000,"index_build_ratio":2.778155580442295,"peak_qps_change_pct":-44.12694171470425,"storage_ratio":2.577576664666139,"to_vectors":2000000},{"demand_ratio":1.4105488075727173,"from_vectors":2000000,"index_build_ratio":2.7149663376776694,"peak_qps_change_pct":-50.14091157146081,"storage_ratio":1.9078136887978512,"to_vectors":3000000}],"schema_version":1,"source_final_analysis_sha256":"135ec7c4ccd12df2c5e955bb61f90db5a1b000c7c5b9c4b0994c3dbe3ad0ac68","source_verification_sha256":"386d7aaf78bb71f0d4e2430001c3dfefbe7435f70f08b0f8131375a7b8b3ae69","status":"verified"}

Peer versions

Peer versions were not recorded in the published result fields.

Evidence digests

Receipt: 17a259d149aa430a00cb3509b479651351b6566e626fe4e20fc0cf8d6a2a9d47
Aggregate: 2fead3b8a6a4640e1877ac0cf3a07c2f2a51444fe5c681d7ba9dedbc052116f8
Provenance: af008fde903f4b2c8b8efed622f0a4a792918d85edcc4118931ab6f721534cca
Harness commit: b3ae41f

Selected measurement

Completed: 8 Oct 2026 · 07:52 UTC
Antfly: main-09b78df97
Runtime: 8h 19m 12s
Platform: linux · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Measurement group

Fast scale

Runtime: 1h 46m 48s across 10 fresh lifecycles; cache-only publication assembly excluded.

Two-lifecycle mean, range, and raw trial values

Antfly main-09b78df97 · 09b78df9

Vectors	Query status	Clean stops / total	Serial p95 ms	Peak QPS queries/s	Peak clients	C30 QPS queries/s	C30 p99 ms	Demand anon + shmem MB	Final volume MB	Build s	Recall min	Selected effort
20,000	ok	2 / 2	4.65 [4.60–4.70]; trials 4.70, 4.60	1,422.66 [1,421.00–1,424.33]; trials 1,421.00, 1,424.33	10, 10	1,352.94 [1,343.27–1,362.62]; trials 1,343.27, 1,362.62	50.97 [50.62–51.32]; trials 51.32, 50.62	1,825.60 [1,825.40–1,825.80]; trials 1,825.80, 1,825.40	84.39 [84.37–84.41]; trials 84.37, 84.41	6.39 [6.17–6.60]; trials 6.60, 6.17	0.9626	0.425, 0.425
40,000	ok	2 / 2	4.90 [4.90–4.90]; trials 4.90, 4.90	1,351.42 [1,307.86–1,394.99]; trials 1,394.99, 1,307.86	20, 10	1,320.63 [1,273.03–1,368.23]; trials 1,368.23, 1,273.03	51.33 [50.01–52.65]; trials 50.01, 52.65	1,746.75 [1,361.00–2,132.50]; trials 2,132.50, 1,361.00	166.19 [165.65–166.74]; trials 165.65, 166.74	12.72 [11.87–13.57]; trials 11.87, 13.57	0.9510	0.4, 0.4
60,000	ok	2 / 2	5.35 [5.20–5.50]; trials 5.50, 5.20	1,298.98 [1,263.27–1,334.69]; trials 1,263.27, 1,334.69	10, 20	1,263.52 [1,222.42–1,304.62]; trials 1,222.42, 1,304.62	54.02 [51.78–56.26]; trials 56.26, 51.78	2,052.05 [1,953.20–2,150.90]; trials 2,150.90, 1,953.20	249.09 [248.82–249.37]; trials 248.82, 249.37	15.58 [15.56–15.59]; trials 15.59, 15.56	0.9552	0.425, 0.4
80,000	ok	2 / 2	5.50 [5.40–5.60]; trials 5.60, 5.40	1,249.47 [1,241.47–1,257.47]; trials 1,257.47, 1,241.47	20, 30	1,237.01 [1,232.54–1,241.47]; trials 1,232.54, 1,241.47	55.16 [53.40–56.92]; trials 56.92, 53.40	2,261.65 [2,226.40–2,296.90]; trials 2,226.40, 2,296.90	329.96 [329.88–330.03]; trials 330.03, 329.88	22.44 [21.45–23.43]; trials 21.45, 23.43	0.9542	0.4, 0.4
100,000	ok	2 / 2	5.75 [5.70–5.80]; trials 5.80, 5.70	1,222.94 [1,207.86–1,238.02]; trials 1,238.02, 1,207.86	20, 20	1,211.14 [1,206.91–1,215.37]; trials 1,215.37, 1,206.91	55.16 [54.07–56.24]; trials 54.07, 56.24	2,229.40 [2,183.00–2,275.80]; trials 2,183.00, 2,275.80	412.93 [412.14–413.73]; trials 413.73, 412.14	26.87 [26.66–27.08]; trials 26.66, 27.08	0.9584	0.4, 0.4

Serial query p95 (1 client)

Antfly main-09b78df97 (09b78df97ec69e020a56110a684b46fce9d4a511) · full ReleaseFast · Zig 0.17.0 · aarch64-linux-musl · baseline CPU · stripped · static · ONNX disabled · Metal disabled · system BLAS disabled · Platform: linux-arm64 · Processor: Apple M4 Max · 20,000–100,000 vectors · 768d · serial after client sweep · seed antfly-circus-vdbbench-v1 · 200 calibration / 800 held-out · 1/5/10/20/30 clients × 30 s · Lower is better

Peak throughput (best client count)

Antfly main-09b78df97 (09b78df97ec69e020a56110a684b46fce9d4a511) · full ReleaseFast · Zig 0.17.0 · aarch64-linux-musl · baseline CPU · stripped · static · ONNX disabled · Metal disabled · system BLAS disabled · Platform: linux-arm64 · Processor: Apple M4 Max · 20,000–100,000 vectors · 768d · best measured client count · seed antfly-circus-vdbbench-v1 · 200 calibration / 800 held-out · 1/5/10/20/30 clients × 30 s · Higher is better

Lifecycle demand (anon + shmem)

Antfly main-09b78df97 (09b78df97ec69e020a56110a684b46fce9d4a511) · full ReleaseFast · Zig 0.17.0 · aarch64-linux-musl · baseline CPU · stripped · static · ONNX disabled · Metal disabled · system BLAS disabled · Platform: linux-arm64 · Processor: Apple M4 Max · 20,000–100,000 vectors · 768d · cgroup anon + shmem peak from pre-index through 1/5/10/20/30-client sweep · seed antfly-circus-vdbbench-v1 · 200 calibration / 800 held-out · 1/5/10/20/30 clients × 30 s · Lower is better

Final database volume

Antfly main-09b78df97 (09b78df97ec69e020a56110a684b46fce9d4a511) · full ReleaseFast · Zig 0.17.0 · aarch64-linux-musl · baseline CPU · stripped · static · ONNX disabled · Metal disabled · system BLAS disabled · Platform: linux-arm64 · Processor: Apple M4 Max · 20,000–100,000 vectors · 768d · post-stop allocated bytes · seed antfly-circus-vdbbench-v1 · 200 calibration / 800 held-out · 1/5/10/20/30 clients × 30 s · Lower is better

Index build time

Antfly main-09b78df97 (09b78df97ec69e020a56110a684b46fce9d4a511) · full ReleaseFast · Zig 0.17.0 · aarch64-linux-musl · baseline CPU · stripped · static · ONNX disabled · Metal disabled · system BLAS disabled · Platform: linux-arm64 · Processor: Apple M4 Max · 20,000–100,000 vectors · 768d · insert + optimize · seed antfly-circus-vdbbench-v1 · 200 calibration / 800 held-out · 1/5/10/20/30 clients × 30 s · Lower is better

Measurement group

Big scale

Runtime: 6h 31m 38s across 14 fresh lifecycles; cache-only publication assembly excluded.

Two-lifecycle mean, range, and raw trial values

Antfly main-09b78df97 · 09b78df9

Vectors	Query status	Clean stops / total	Serial p95 ms	Peak QPS queries/s	Peak clients	C30 QPS queries/s	C30 p99 ms	Demand anon + shmem MB	Final volume MB	Build s	Recall min	Selected effort
200,000	ok	2 / 2	6.30 [6.20–6.40]; trials 6.20, 6.40	1,184.65 [1,176.76–1,192.53]; trials 1,192.53, 1,176.76	20, 20	1,171.90 [1,153.01–1,190.80]; trials 1,190.80, 1,153.01	57.41 [55.50–59.32]; trials 55.50, 59.32	2,391.90 [2,107.40–2,676.40]; trials 2,676.40, 2,107.40	907.71 [905.54–909.89]; trials 909.89, 905.54	54.68 [54.22–55.14]; trials 54.22, 55.14	0.9548	0.375, 0.375
400,000	ok	2 / 2	7.25 [7.20–7.30]; trials 7.20, 7.30	1,047.35 [1,040.70–1,054.00]; trials 1,040.70, 1,054.00	30, 20	1,030.23 [1,019.75–1,040.70]; trials 1,040.70, 1,019.75	63.09 [62.29–63.89]; trials 62.29, 63.89	2,621.35 [2,412.90–2,829.80]; trials 2,829.80, 2,412.90	1,972.83 [1,971.29–1,974.37]; trials 1,971.29, 1,974.37	119.74 [118.79–120.69]; trials 118.79, 120.69	0.9636	0.375, 0.375
600,000	ok	2 / 2	8.65 [7.90–9.40]; trials 9.40, 7.90	905.48 [901.39–909.57]; trials 909.57, 901.39	30, 30	905.48 [901.39–909.57]; trials 909.57, 901.39	71.57 [70.86–72.28]; trials 72.28, 70.86	2,845.25 [2,820.00–2,870.50]; trials 2,870.50, 2,820.00	3,107.81 [3,098.08–3,117.53]; trials 3,117.53, 3,098.08	211.00 [209.69–212.31]; trials 209.69, 212.31	0.9592	0.375, 0.375
800,000	ok	2 / 2	10.45 [9.60–11.30]; trials 9.60, 11.30	810.17 [797.19–823.16]; trials 797.19, 823.16	30, 20	806.27 [797.19–815.34]; trials 797.19, 815.34	80.72 [77.35–84.09]; trials 84.09, 77.35	3,701.25 [3,464.20–3,938.30]; trials 3,464.20, 3,938.30	4,328.11 [4,260.02–4,396.20]; trials 4,260.02, 4,396.20	303.03 [292.87–313.19]; trials 292.87, 313.19	0.9667	0.4, 0.4
1,000,000	ok	2 / 2	11.75 [11.10–12.40]; trials 12.40, 11.10	796.79 [795.11–798.47]; trials 798.47, 795.11	30, 20	790.96 [783.45–798.47]; trials 798.47, 783.45	86.30 [82.06–90.54]; trials 82.06, 90.54	3,911.85 [3,842.20–3,981.50]; trials 3,842.20, 3,981.50	6,094.61 [5,936.89–6,252.32]; trials 6,252.32, 5,936.89	403.56 [386.67–420.45]; trials 386.67, 420.45	0.9606	0.4, 0.4
2,000,000	ok	2 / 2	26.25 [22.70–29.80]; trials 29.80, 22.70	445.19 [331.97–558.41]; trials 558.41, 331.97	20, 30	334.95 [331.97–337.93]; trials 337.93, 331.97	465.92 [286.04–645.80]; trials 286.04, 645.80	6,528.70 [6,241.00–6,816.40]; trials 6,241.00, 6,816.40	15,709.32 [15,575.86–15,842.78]; trials 15,842.78, 15,575.86	1,121.16 [1,063.72–1,178.60]; trials 1,063.72, 1,178.60	0.9596	0.425, 0.425
3,000,000	ok	2 / 2	26.95 [19.30–34.60]; trials 34.60, 19.30	221.97 [113.90–330.03]; trials 113.90, 330.03	30, 30	221.97 [113.90–330.03]; trials 113.90, 330.03	1,131.24 [461.08–1,801.40]; trials 1,801.40, 461.08	9,209.05 [9,190.70–9,227.40]; trials 9,227.40, 9,190.70	29,970.45 [29,578.32–30,362.57]; trials 29,578.32, 30,362.57	3,043.90 [2,878.87–3,208.94]; trials 3,208.94, 2,878.87	0.9624	0.45, 0.45

Serial query p95 (1 client)

Antfly main-09b78df97 (09b78df97ec69e020a56110a684b46fce9d4a511) · full ReleaseFast · Zig 0.17.0 · aarch64-linux-musl · baseline CPU · stripped · static · ONNX disabled · Metal disabled · system BLAS disabled · Platform: linux-arm64 · Processor: Apple M4 Max · 200,000–3,000,000 vectors · 768d · serial after client sweep · seed antfly-circus-vdbbench-v1 · 200 calibration / 800 held-out · 1/5/10/20/30 clients × 30 s · Lower is better

Peak throughput (best client count)

Antfly main-09b78df97 (09b78df97ec69e020a56110a684b46fce9d4a511) · full ReleaseFast · Zig 0.17.0 · aarch64-linux-musl · baseline CPU · stripped · static · ONNX disabled · Metal disabled · system BLAS disabled · Platform: linux-arm64 · Processor: Apple M4 Max · 200,000–3,000,000 vectors · 768d · best measured client count · seed antfly-circus-vdbbench-v1 · 200 calibration / 800 held-out · 1/5/10/20/30 clients × 30 s · Higher is better

Lifecycle demand (anon + shmem)

Antfly main-09b78df97 (09b78df97ec69e020a56110a684b46fce9d4a511) · full ReleaseFast · Zig 0.17.0 · aarch64-linux-musl · baseline CPU · stripped · static · ONNX disabled · Metal disabled · system BLAS disabled · Platform: linux-arm64 · Processor: Apple M4 Max · 200,000–3,000,000 vectors · 768d · cgroup anon + shmem peak from pre-index through 1/5/10/20/30-client sweep · seed antfly-circus-vdbbench-v1 · 200 calibration / 800 held-out · 1/5/10/20/30 clients × 30 s · Lower is better

Final database volume

Antfly main-09b78df97 (09b78df97ec69e020a56110a684b46fce9d4a511) · full ReleaseFast · Zig 0.17.0 · aarch64-linux-musl · baseline CPU · stripped · static · ONNX disabled · Metal disabled · system BLAS disabled · Platform: linux-arm64 · Processor: Apple M4 Max · 200,000–3,000,000 vectors · 768d · post-stop allocated bytes · seed antfly-circus-vdbbench-v1 · 200 calibration / 800 held-out · 1/5/10/20/30 clients × 30 s · Lower is better

Index build time

Antfly main-09b78df97 (09b78df97ec69e020a56110a684b46fce9d4a511) · full ReleaseFast · Zig 0.17.0 · aarch64-linux-musl · baseline CPU · stripped · static · ONNX disabled · Metal disabled · system BLAS disabled · Platform: linux-arm64 · Processor: Apple M4 Max · 200,000–3,000,000 vectors · 768d · insert + optimize · seed antfly-circus-vdbbench-v1 · 200 calibration / 800 held-out · 1/5/10/20/30 clients × 30 s · Lower is better

vector-filtered-ann

complete

Filtered ANN

Antfly main-09b78df97, stripped ReleaseFast, passed three fresh tenant-scoped filtered ANN lifecycles at a 30-client ceiling with zero request errors: recall 1.000, mean peak throughput 327.03 QPS, and mean service memory demand 728.2 MB.

Methodology scope · protocol · interpretation

Tenant-scoped filtered ANN publication protocol

The workload contains 50,000 1,536-dimensional cosine vectors in 100 equal tenant buckets. Each top-100 query searches one rotating 500-vector tenant. Each of three fresh Linux ARM64 lifecycles builds one index, tunes only on 200 deterministic calibration queries, and measures the disjoint 800-query publication holdout without rebuilding. The complete publication sweep uses 1, 8, and 30 clients for 10 seconds per point, plus a serial pass. Every lifecycle must complete the declared sweep with zero request errors; the default full-text index is retained and verified through the public API.

Performance and resource values are arithmetic means with three-trial ranges. Database-service memory demand is concurrent cgroup anon + shmem sampled from before indexing through publication, excluding the benchmark client. Final database volume is checksum-verified post-stop allocated bytes across the complete declared volume. Results do not establish capacity above 30 clients.

Peer rows retain their historical identities and measurement dates; they are references, not fresh matched comparisons.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: vector-filtered-ann
Domain: vector/filtered-ann
Source: https://github.com/antflydb/VectorDBBench
Upstream: https://github.com/zilliztech/VectorDBBench
Known Antfly versions: v0.2.*
Expected duration: 270 min
Enabled: yes

Benchmark parameters

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Trial variation

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Peer versions

1.39.2
9.5.2
v2.6.22
0.8.6-pg16
1.5.9

Evidence digests

Receipt: a85438092e7cca9d7461ef2f1adf5901a131586c057b5e78ae909da688d5883a
Aggregate: 53ad272473dd9b610a969e80835f5d59b0e7a97d05afff2ec7ec48360812839f
Provenance: 53ad272473dd9b610a969e80835f5d59b0e7a97d05afff2ec7ec48360812839f
Harness commit: 82c699bb7a687b65efc691ec329368494ce8499e

Peer cohort evidence · 1536d-50K-tenant-scoped-1pct

Completed: 31 Aug 2026 · 16:11 UTC
Fresh lifecycles: 15
Peer variants: 5
Receipt: 069d2e8eb1e613e4c513af08320564af81dd4a41d8991adddcd7064db043f85b
Aggregate: 04d4f8a9071bf1fd4abf048b985f02d332a6eefa68560aaea086f67568f43c96
Provenance: 04d4f8a9071bf1fd4abf048b985f02d332a6eefa68560aaea086f67568f43c96

Selected measurement

Completed: 7 Oct 2026 · 02:14 UTC
Antfly: main-09b78df97 · 6 October 2026 · 00:55 UTC
Runtime: 28m 50s
Platform: linux · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Peer cohort · 1536d-50K-tenant-scoped-1pct

Completed: 31 Aug 2026 · 16:11 UTC
Variants: 5 independently executed peers
Lifecycles: 15 fresh
Compatibility: Historical reference · not a matched runtime

Peak filtered throughput

Antfly main-09b78df97 (09b78df9, ReleaseFast/stripped) · linux-arm64 · tenant-scoped 1536d/50K · 3 fresh lifecycles · 1/8/30 clients · 10 s/point · partition seed antfly-circus-vdbbench-v1 · Higher is better · Apple M4 Max · podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Peak-concurrency p99

Antfly main-09b78df97 (09b78df9, ReleaseFast/stripped) · linux-arm64 · tenant-scoped 1536d/50K · 3 fresh lifecycles · 1/8/30 clients · 10 s/point · partition seed antfly-circus-vdbbench-v1 · Lower is better · Apple M4 Max · podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Demand working set

Antfly main-09b78df97 (09b78df9, ReleaseFast/stripped) · linux-arm64 · tenant-scoped 1536d/50K · 3 fresh lifecycles · 1/8/30 clients · 10 s/point · partition seed antfly-circus-vdbbench-v1 · Lower is better · Apple M4 Max · podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Tenant-scoped filtered ANN

Antfly main-09b78df97 · 09b78df9

Engine	Recall@100	nDCG	Peak QPS queries/s	Peak p99 ms	Serial p99 ms	Demand MB	Final volume MB	Trials
Antfly	1.0000	1.0000	327.0	177.90	23.20	728.2	369.0	3
Weaviate	1.0000	1.0000	1,143.9	11.71	6.73	962.6	392.7	3
Elasticsearch	1.0000	1.0000	5,810.7	13.51	1.80	1,912.8	312.4	3
Milvus	1.0000	1.0000	6,789.3	9.16	1.50	2,980.8	2,394.2	3
pgvector	0.9573	0.9661	167.6	224.49	56.07	2,303.7	1,524.0	3
Chroma	0.9999	0.9999	111.6	573.43	79.97	499.9	336.1	3

III

fulltext-search-benchmark-game

partial

Search Benchmark Game

Retained August 27 Antfly v0.2.1-rc1 results over 250,000 Wikipedia documents, four query classes, two result windows, and two concurrency levels.

Methodology scope · protocol · interpretation

Search Benchmark Game Methodology

What this lane measures

This is an end-to-end, self-hosted database comparison over the first 250,000 documents in the Search Benchmark Game Wikipedia corpus. Every timed adapter uses a persistent database connection and requests ranked document IDs without stored document bodies. Tantivy is deliberately absent: it is an embedded search library, while every measured row here is a database service.

The run uses the 902 upstream term, union, intersection, and phrase queries. The 60 mixed required/optional and negated Lucene-syntax queries remain excluded because Antfly cannot represent their matching and scoring semantics directly. If the remaining workload proves too Lucene-oriented for database comparison, that will motivate a separate benchmark rather than further changing this one.

Database matrix and capability policy

Antfly 0.2.0-rc.18: term, union, intersection, phrase
Elasticsearch 8.15.3: term, union, intersection, phrase
Weaviate 1.38.2: term, union, intersection; exact phrase unsupported
Quickwit 0.8.2: term, union, intersection, phrase
PostgreSQL 16 from the pgvector image: term, union, intersection, phrase; pgvector is not involved in lexical execution
Milvus 2.5.8: retained as unsupported because its BM25 raw-text input is a VARCHAR capped at 65,535 bytes, while 20 corpus documents exceed that limit and the maximum is 202,798 bytes
Chroma self-hosted: retained as unsupported because its text surface provides containment/regex filtering rather than ranked lexical top-k retrieval; the richer Chroma Search API is cloud-only

Missing capabilities are never emulated client-side. Public output uses —* for a product limitation and failed† for a setup or execution failure, with the reason preserved in JSON and rendered beside the table.

Execution protocol

The benchmark runs TOP_10 and TOP_100 at concurrency 1 and 8. Each cell has a five-second warmup followed by two measured rounds. Concurrency uses one persistent connection per worker; individual request latency and aggregate QPS are both recorded. Only one database is timed at once. Indexing is sequential, uses the unchanged corpus, and uses native bulk paths (COPY for PostgreSQL, bulk APIs elsewhere).

Antfly uses a prebuilt release binary; the benchmark never builds Zig. It runs one shard and sends fields: []. Elasticsearch uses one primary shard, zero replicas, a 1 GiB heap, and a one-segment force merge. Weaviate runs one node with vectorization disabled. Quickwit runs one node with a positional, fieldnorm-enabled text index and BM25 score ordering; only external IDs are stored. PostgreSQL uses a stored tsvector, GIN index, and ts_rank_cd ordering.

Where configurable, adapters approximate Antfly’s fixed Bleve analyzer with standard/word tokenization, lowercase normalization, and English stopwords. Quickwit’s built-in default tokenizer lowercases but does not expose a matching stop-word filter. Residual analyzer and scoring differences are reported through an untimed top-10 ID/count diagnostic; exact cross-engine ranking is not a pass condition.

Interpretation

The headline table shows TOP_10 concurrency-8 p95 latency by query class so partial capability is visible. Full artifacts retain p50/p95/p99, QPS, sample counts, status, and reasons for TOP_10/TOP_100 at both concurrency levels. This benchmark has no relevance judgments, so it supports performance and capability claims only—not claims that one engine ranks documents more correctly.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: fulltext-search-benchmark-game
Domain: full-text
Source: https://github.com/quickwit-oss/search-benchmark-game
Known Antfly versions: v0.1.3, v0.2.*
Enabled: yes

Benchmark parameters

{"concurrency":[1,8],"corpus_documents":250000,"engine_details":{},"query_classes":["term","union","intersection","phrase"],"result_windows":["TOP_10","TOP_100"]}

Peer versions

Elasticsearch8.15.3
Weaviate1.38.2
Quickwit0.8.2
PostgreSQL16
Milvus2.5.8

Evidence digests

Receipt: 497cd5bb71933a4870d77594d3a9077af7a3a873d7c1b03e20ab84c8f0a9fb66
Aggregate: 0d60283a261325d0d59a95e51fb47259572da07982813583531dc65b75607a17
Provenance: 121237470c0ad51498a070266c901994203dde752a1344072f5ce967c4f25514
Harness commit: 099cb05da1d0503fcd47ee5f454b0bde617b5529

Selected partial evidence

Completed: 27 Aug 2026 · 10:42 UTC
Antfly: v0.2.1-rc1 · 26 August 2026 · 20:47 UTC
Runtime: 2m 54s
Platform: darwin · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Top 10 · concurrency 1

Antfly v0.2.1-rc1 (279381f7, ReleaseFast/full) · darwin-arm64 · Apple M4 Max · 250,000 documents · 902-query workload · QPS, higher is better

Top 10 · concurrency 8

Antfly v0.2.1-rc1 (279381f7, ReleaseFast/full) · darwin-arm64 · Apple M4 Max · 250,000 documents · 902-query workload · QPS, higher is better

Top 100 · concurrency 1

Antfly v0.2.1-rc1 (279381f7, ReleaseFast/full) · darwin-arm64 · Apple M4 Max · 250,000 documents · 902-query workload · QPS, higher is better

Top 100 · concurrency 8

Antfly v0.2.1-rc1 (279381f7, ReleaseFast/full) · darwin-arm64 · Apple M4 Max · 250,000 documents · 902-query workload · QPS, higher is better

Search behavior by query class and result window

Antfly v0.2.1-rc1 · 279381f7

Engine	Query class	Result window	Concurrency	Queries	QPS	p95 ms	Status
Antfly	term	TOP_10	1	1	5,972.4	0.121	measured
Antfly	union	TOP_10	1	301	1,369.6	2.739	measured
Antfly	intersection	TOP_10	1	300	2,174.5	1.482	measured
Antfly	phrase	TOP_10	1	300	3,940.1	0.465	measured
Antfly	term	TOP_10	8	1	6,111.5	0.124	measured
Antfly	union	TOP_10	8	301	8,039.7	3.478	measured
Antfly	intersection	TOP_10	8	300	12,925.1	1.655	measured
Antfly	phrase	TOP_10	8	300	21,324.5	0.720	measured
Antfly	term	TOP_100	1	1	6,149.1	0.123	measured
Antfly	union	TOP_100	1	301	1,164.7	3.057	measured
Antfly	intersection	TOP_100	1	300	2,049.7	1.675	measured
Antfly	phrase	TOP_100	1	300	3,618.4	0.507	measured
Antfly	term	TOP_100	8	1	4,417.0	0.221	measured
Antfly	union	TOP_100	8	301	7,020.0	3.605	measured
Antfly	intersection	TOP_100	8	300	12,444.2	1.736	measured
Antfly	phrase	TOP_100	8	300	20,502.3	0.722	measured
weaviate-1.38.2	term	TOP_10	1	1	586.6	1.829	measured
weaviate-1.38.2	union	TOP_10	1	301	1,151.5	1.177	measured
weaviate-1.38.2	intersection	TOP_10	1	300	1,103.3	1.196	measured
weaviate-1.38.2	phrase	TOP_10	1	300	Unsupported	Unsupported	unsupported
quickwit-0.8.2	term	TOP_10	1	1	318.3	3.104	measured
quickwit-0.8.2	union	TOP_10	1	301	326.7	3.357	measured
quickwit-0.8.2	intersection	TOP_10	1	300	381.9	3.282	measured
quickwit-0.8.2	phrase	TOP_10	1	300	586.3	3.037	measured
postgresql-16	term	TOP_10	1	1	3,472.5	0.240	measured
postgresql-16	union	TOP_10	1	301	13.8	215.429	measured
postgresql-16	intersection	TOP_10	1	300	511.4	6.565	measured
postgresql-16	phrase	TOP_10	1	300	534.6	5.612	measured
milvus-2.5.8	term	TOP_10	1	1	Unsupported	Unsupported	unsupported
milvus-2.5.8	union	TOP_10	1	301	Unsupported	Unsupported	unsupported
milvus-2.5.8	intersection	TOP_10	1	300	Unsupported	Unsupported	unsupported
milvus-2.5.8	phrase	TOP_10	1	300	Unsupported	Unsupported	unsupported
chroma-self-hosted	term	TOP_10	1	1	Unsupported	Unsupported	unsupported
chroma-self-hosted	union	TOP_10	1	301	Unsupported	Unsupported	unsupported
chroma-self-hosted	intersection	TOP_10	1	300	Unsupported	Unsupported	unsupported
chroma-self-hosted	phrase	TOP_10	1	300	Unsupported	Unsupported	unsupported
weaviate-1.38.2	term	TOP_10	8	1	905.6	0.909	measured
weaviate-1.38.2	union	TOP_10	8	301	6,874.6	1.537	measured
weaviate-1.38.2	intersection	TOP_10	8	300	6,955.8	1.690	measured
weaviate-1.38.2	phrase	TOP_10	8	300	Unsupported	Unsupported	unsupported
quickwit-0.8.2	term	TOP_10	8	1	296	3.286	measured
quickwit-0.8.2	union	TOP_10	8	301	1,762	5.956	measured
quickwit-0.8.2	intersection	TOP_10	8	300	2,019	5.318	measured
quickwit-0.8.2	phrase	TOP_10	8	300	2,460.8	5.227	measured
postgresql-16	term	TOP_10	8	1	3,481	0.239	measured
postgresql-16	union	TOP_10	8	301	76.2	311.210	measured
postgresql-16	intersection	TOP_10	8	300	2,268.7	10.292	measured
postgresql-16	phrase	TOP_10	8	300	2,411.9	8.667	measured
milvus-2.5.8	term	TOP_10	8	1	Unsupported	Unsupported	unsupported
milvus-2.5.8	union	TOP_10	8	301	Unsupported	Unsupported	unsupported
milvus-2.5.8	intersection	TOP_10	8	300	Unsupported	Unsupported	unsupported
milvus-2.5.8	phrase	TOP_10	8	300	Unsupported	Unsupported	unsupported
chroma-self-hosted	term	TOP_10	8	1	Unsupported	Unsupported	unsupported
chroma-self-hosted	union	TOP_10	8	301	Unsupported	Unsupported	unsupported
chroma-self-hosted	intersection	TOP_10	8	300	Unsupported	Unsupported	unsupported
chroma-self-hosted	phrase	TOP_10	8	300	Unsupported	Unsupported	unsupported
weaviate-1.38.2	term	TOP_100	1	1	837	0.963	measured
weaviate-1.38.2	union	TOP_100	1	301	621.5	2.115	measured
weaviate-1.38.2	intersection	TOP_100	1	300	797.2	1.984	measured
weaviate-1.38.2	phrase	TOP_100	1	300	Unsupported	Unsupported	unsupported
quickwit-0.8.2	term	TOP_100	1	1	49.2	20.797	measured
quickwit-0.8.2	union	TOP_100	1	301	53.4	21.169	measured
quickwit-0.8.2	intersection	TOP_100	1	300	111.5	19.710	measured
quickwit-0.8.2	phrase	TOP_100	1	300	327.4	14.740	measured
postgresql-16	term	TOP_100	1	1	3,519.6	0.236	measured
postgresql-16	union	TOP_100	1	301	13.6	220.023	measured
postgresql-16	intersection	TOP_100	1	300	482.5	6.983	measured
postgresql-16	phrase	TOP_100	1	300	529.3	5.977	measured
milvus-2.5.8	term	TOP_100	1	1	Unsupported	Unsupported	unsupported
milvus-2.5.8	union	TOP_100	1	301	Unsupported	Unsupported	unsupported
milvus-2.5.8	intersection	TOP_100	1	300	Unsupported	Unsupported	unsupported
milvus-2.5.8	phrase	TOP_100	1	300	Unsupported	Unsupported	unsupported
chroma-self-hosted	term	TOP_100	1	1	Unsupported	Unsupported	unsupported
chroma-self-hosted	union	TOP_100	1	301	Unsupported	Unsupported	unsupported
chroma-self-hosted	intersection	TOP_100	1	300	Unsupported	Unsupported	unsupported
chroma-self-hosted	phrase	TOP_100	1	300	Unsupported	Unsupported	unsupported
weaviate-1.38.2	term	TOP_100	8	1	2,046.7	0.448	measured
weaviate-1.38.2	union	TOP_100	8	301	3,145.7	4.015	measured
weaviate-1.38.2	intersection	TOP_100	8	300	4,033.2	3.467	measured
weaviate-1.38.2	phrase	TOP_100	8	300	Unsupported	Unsupported	unsupported
quickwit-0.8.2	term	TOP_100	8	1	50.7	19.463	measured
quickwit-0.8.2	union	TOP_100	8	301	373	24.984	measured
quickwit-0.8.2	intersection	TOP_100	8	300	749.4	21.959	measured
quickwit-0.8.2	phrase	TOP_100	8	300	1,783.1	17.652	measured
postgresql-16	term	TOP_100	8	1	3,285	0.265	measured
postgresql-16	union	TOP_100	8	301	73.9	322.166	measured
postgresql-16	intersection	TOP_100	8	300	2,309.4	10.066	measured
postgresql-16	phrase	TOP_100	8	300	2,328.8	8.822	measured
milvus-2.5.8	term	TOP_100	8	1	Unsupported	Unsupported	unsupported
milvus-2.5.8	union	TOP_100	8	301	Unsupported	Unsupported	unsupported
milvus-2.5.8	intersection	TOP_100	8	300	Unsupported	Unsupported	unsupported
milvus-2.5.8	phrase	TOP_100	8	300	Unsupported	Unsupported	unsupported
chroma-self-hosted	term	TOP_100	8	1	Unsupported	Unsupported	unsupported
chroma-self-hosted	union	TOP_100	8	301	Unsupported	Unsupported	unsupported
chroma-self-hosted	intersection	TOP_100	8	300	Unsupported	Unsupported	unsupported
chroma-self-hosted	phrase	TOP_100	8	300	Unsupported	Unsupported	unsupported

inference-termite-circus

complete

Inference

Antfly v0.2.1-rc.3 passed all seven requested inference workloads across 21 fresh lifecycles.

Methodology scope · protocol · interpretation

Antfly Inference Methodology

Subject contract

Inference is delegated to ../termite-circus. Each campaign receives exactly one explicit ANTFLY_BIN from the antfly-circus subject manifest. The harness records the executable’s version, architecture, and SHA-256; it does not fetch, install, update, or build Antfly. Comparing Antfly releases means comparing separate campaign bundles.

The rc.24 acceptance matrix covers generation, dense/sparse/multimodal embedding, reranking, chunking, GLiNER2 extraction, OCR/readers, and transcription. Rewriters are reported as known-incompatible rather than timed.

Profiles

smoke runs only the supplied Antfly binary, one lifecycle and one measured request, against one certified representative per working category. It is a compatibility gate, not publication evidence.
full adds category-appropriate local reference runtimes and certified model alternates. Each provider/model cell uses three fresh lifecycles, one warmup per lifecycle, and the tracked request count from matrix.json. Provider order alternates to reduce order bias.

Reference runtimes are local only: llama.cpp, Ollama, and vLLM-Metal for generation; ONNX Runtime and Sentence Transformers for embedding/reranking; GLiNER2 for extraction; Transformers for Florence-2; and faster-whisper plus whisper.cpp for transcription.

Provider-native formats are permitted when a runtime cannot load an identical artifact. Every result retains the logical model, exact artifact/revision, variant or quantization, and checksum. Such rows are not described as byte-identical comparisons.

Validity and metrics

Every cell must pass a deterministic category-specific quality gate before its latency or throughput is valid. The gates check semantic ordering, sparse output, cross-modal output, relevant-document ordering, valid chunk coverage, expected extraction fields, OCR/transcription word recovery, or a nonempty constrained completion. These fixtures detect broken inference; they are not a general model-quality leaderboard.

Warm request latency is reported as p50 and p95 within measured requests. Throughput uses successful measured requests only. Cold model-load/readiness time and raw provider output remain in the campaign artifacts rather than being mixed into warm latency.

Peak inference memory is the maximum of two concurrently sampled views:

rooted process-tree RSS, including provider helpers and model servers;
positive growth in system anonymous + compressor-occupied + wired memory from the pre-launch baseline.

Samples are retained every 200 ms. System growth is publishable only when the operator sets QUIET_HOST_ACK=1 on a quiet host; otherwise the memory value is diagnostic. Full reports retain each lifecycle and report the arithmetic mean and range rather than selecting the best trial.

Artifacts

The full antfly-circus command writes directly into $BASTILLE_OUT/data/inference-termite-circus/:

report.md: compact per-category tables;
result.json: canonical normalized rows consumed by antfly-circus;
provenance.json: subject, host, model, provider, and input fingerprints;
receipt.json: completeness, failures, and quality-gate status;
raw/: provider logs and memory timelines.

A failed campaign still retains the bundle and failed rows. Publication reads result.json and the receipt; Markdown is derived output and is never parsed as the source of truth.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: inference-termite-circus
Domain: inference
Source: https://github.com/antflydb/termite-circus
Known Antfly versions: v0.2.*
Enabled: yes

Benchmark parameters

{"completed_workloads":7,"failed_workloads":0,"memory_metric":"max-rooted-RSS-and-positive-system-anonymous-compressor-wired-growth","memory_unit":"MB","model_artifacts":[{"artifact_sha256":"676c35070db6dbe52f93e9c864ee0fba4eddea94b9c875d9cb10daff453fbaee","benchmark_id":"generation-gemma4-e4b-qat","model":"google/gemma-4-E4B-it-qat-q4_0-gguf","variant":"QAT q4_0"},{"artifact_sha256":"449c8a2f7115155ad21291a887c8c7a136b0642f598a910018a37978c167d934","benchmark_id":"dense-bge-small","model":"BAAI/bge-small-en-v1.5","variant":"f32"},{"artifact_sha256":"a00e24a8e937f7f25434403396a3ac7ba76ffb4917b7403f629007168dbe611c","benchmark_id":"sparse-splade-tiny","model":"sparse-encoder-testing/splade-bert-tiny-nq-onnx","variant":"onnx"},{"artifact_sha256":"e27744c7a1716a21a6652de9b17d01b8773e782230faeefaae7947f7b7c7961a","benchmark_id":"rerank-mxbai-base","model":"mixedbread-ai/mxbai-rerank-base-v1","variant":"f32"},{"artifact_sha256":null,"benchmark_id":"chunk-fixed-bert","model":"fixed_bert","variant":"built-in"},{"artifact_sha256":"0eb40d545ed9a3849d76e49104ae6f3e1b4702bb96394ab1afff6b641dd9477b","benchmark_id":"extract-gliner2-base","model":"antflydb/gliner2-base-v1","variant":"f32"},{"artifact_sha256":"868e1ad35ae82615228c7d3503c9ed1e7310804b72b9a85ddc604af546ca5958","benchmark_id":"transcribe-whisper-tiny","model":"openai/whisper-tiny","variant":"f32"}],"planned_workloads":7,"source_memory_unit":"MiB","trials_per_workload":3,"workloads":[{"chat_template_kwargs":{"enable_thinking":false},"host_budget_mb":8192,"id":"generation-gemma4-e4b-qat","model":"google/gemma-4-E4B-it-qat-q4_0-gguf","variant":"QAT q4_0"},{"id":"dense-bge-small","model":"BAAI/bge-small-en-v1.5","variant":"f32"},{"id":"sparse-splade-tiny","model":"sparse-encoder-testing/splade-bert-tiny-nq-onnx","variant":"onnx"},{"id":"rerank-mxbai-base","model":"mixedbread-ai/mxbai-rerank-base-v1","variant":"f32"},{"id":"chunk-fixed-bert","model":"fixed_bert","variant":"built-in"},{"id":"extract-gliner2-base","model":"antflydb/gliner2-base-v1","variant":"f32"},{"id":"transcribe-whisper-tiny","model":"openai/whisper-tiny","variant":"f32"}]}

Trial variation

[{"model":"ggml-org/gemma-4-E4B-it-GGUF","peak_memory":{"maximum":7726.65625,"mean":7434.364583333333,"minimum":7111,"unit":"MB"},"provider":"llama.cpp","variant":"Q4_0"},{"model":"ggml-org/gemma-4-E4B-it-GGUF","peak_memory":{"maximum":11632.296875,"mean":10929.015625,"minimum":10415.78125,"unit":"MB"},"provider":"ollama","variant":"Q4_0"},{"model":"ggml-org/gemma-4-E4B-it-GGUF","peak_memory":{"maximum":27998.640625,"mean":25524.130208333332,"minimum":20975.46875,"unit":"MB"},"provider":"vllm-metal","variant":"Q4_0"},{"model":"google/gemma-4-E4B-it-qat-q4_0-gguf","peak_memory":{"maximum":8404.0625,"mean":7605.09375,"minimum":7201.640625,"unit":"MB"},"provider":"llama.cpp","variant":"QAT q4_0"},{"model":"google/gemma-4-E4B-it-qat-q4_0-gguf","peak_memory":{"maximum":7804.75,"mean":7387.28125,"minimum":6806.921875,"unit":"MB"},"provider":"ollama","variant":"QAT q4_0"},{"model":"google/gemma-4-E4B-it-qat-q4_0-gguf","peak_memory":{"maximum":28953.59375,"mean":28351.203125,"minimum":28043.796875,"unit":"MB"},"provider":"vllm-metal","variant":"QAT q4_0"},{"model":"unsloth/Qwen3-1.7B-GGUF","peak_memory":{"maximum":5665.421875,"mean":5665.348958333333,"minimum":5665.25,"unit":"MB"},"provider":"llama.cpp","variant":"Q4_K_M"},{"model":"unsloth/Qwen3-1.7B-GGUF","peak_memory":{"maximum":5348.796875,"mean":5162.703125,"minimum":5059.1875,"unit":"MB"},"provider":"ollama","variant":"Q4_K_M"},{"model":"unsloth/Qwen3-1.7B-GGUF","peak_memory":{"maximum":28489.640625,"mean":25832.145833333332,"minimum":24216.65625,"unit":"MB"},"provider":"vllm-metal","variant":"Q4_K_M"},{"model":"BAAI/bge-small-en-v1.5","peak_memory":{"maximum":1027.65625,"mean":1024.2864583333333,"minimum":1022.125,"unit":"MB"},"provider":"onnxruntime","variant":"f32"},{"model":"BAAI/bge-small-en-v1.5","peak_memory":{"maximum":1734.4375,"mean":1296.7708333333333,"minimum":531.328125,"unit":"MB"},"provider":"sentence-transformers","variant":"f32"},{"model":"BAAI/bge-large-en-v1.5","peak_memory":{"maximum":3448.859375,"mean":3448.4322916666665,"minimum":3448.21875,"unit":"MB"},"provider":"onnxruntime","variant":"f32"},{"model":"BAAI/bge-large-en-v1.5","peak_memory":{"maximum":3779.78125,"mean":2297.2447916666665,"minimum":534.21875,"unit":"MB"},"provider":"sentence-transformers","variant":"f32"},{"model":"mixedbread-ai/mxbai-embed-large-v1","peak_memory":{"maximum":3447.1875,"mean":3446.8854166666665,"minimum":3446.671875,"unit":"MB"},"provider":"onnxruntime","variant":"f32"},{"model":"mixedbread-ai/mxbai-embed-large-v1","peak_memory":{"maximum":3188.9375,"mean":2633.1770833333335,"minimum":1609.125,"unit":"MB"},"provider":"sentence-transformers","variant":"f32"},{"model":"sparse-encoder-testing/splade-bert-tiny-nq-onnx","peak_memory":{"maximum":630.59375,"mean":628.4947916666666,"minimum":626.75,"unit":"MB"},"provider":"onnxruntime","variant":"onnx"},{"model":"sparse-encoder-testing/splade-bert-tiny-nq-onnx","peak_memory":{"maximum":1570.609375,"mean":1275.5416666666667,"minimum":707,"unit":"MB"},"provider":"sentence-transformers","variant":"onnx"},{"model":"mixedbread-ai/mxbai-rerank-base-v1","peak_memory":{"maximum":4774.015625,"mean":4766.505208333333,"minimum":4760.4375,"unit":"MB"},"provider":"onnxruntime","variant":"f32"},{"model":"mixedbread-ai/mxbai-rerank-base-v1","peak_memory":{"maximum":2340.1875,"mean":1827.171875,"minimum":1177.53125,"unit":"MB"},"provider":"sentence-transformers","variant":"f32"},{"model":"cross-encoder/ms-marco-MiniLM-L6-v2","peak_memory":{"maximum":962.453125,"mean":960.0885416666666,"minimum":958.375,"unit":"MB"},"provider":"onnxruntime","variant":"f32"},{"model":"cross-encoder/ms-marco-MiniLM-L6-v2","peak_memory":{"maximum":1560.453125,"mean":886.6770833333334,"minimum":521.984375,"unit":"MB"},"provider":"sentence-transformers","variant":"f32"},{"model":"fixed_bert","peak_memory":{"maximum":205.90625,"mean":205.58854166666666,"minimum":205.328125,"unit":"MB"},"provider":"tokenizers","variant":"built-in"},{"model":"fixed_bpe","peak_memory":{"maximum":206.234375,"mean":205.75,"minimum":205.5,"unit":"MB"},"provider":"tokenizers","variant":"built-in"},{"model":"mirth/chonky_mmbert_small_multilingual_1","peak_memory":{"maximum":635.234375,"mean":623.4427083333334,"minimum":600.0625,"unit":"MB"},"provider":"tokenizers","variant":"f32"},{"model":"antflydb/gliner2-base-v1","peak_memory":{"maximum":1779.546875,"mean":1401.1354166666667,"minimum":1211.796875,"unit":"MB"},"provider":"gliner2","variant":"f32"},{"model":"openai/whisper-tiny","peak_memory":{"maximum":498.125,"mean":394.1822916666667,"minimum":188.6875,"unit":"MB"},"provider":"whisper.cpp","variant":"f32"}]

Peer versions

llama.cppb9870 (2d973636e)
Ollama0.31.1
vLLM-Metal0.3.0.dev20260811042359 (vLLM 0.27.0+cpu)
ONNX Runtime1.28.0
Sentence Transformers5.6.1
Transformers tokenizer4.45.2
GLiNER21.3.2
Transformers4.45.2
faster-whisper1.2.1
whisper.cpp1.9.2

Evidence digests

Receipt: 30b6bfe680483a57b338b4f29496a03ad7d403df37675515cf220a4b79e53fd3
Aggregate: 2cf17806a20af41156fb7fbba9c2c9451ccfe43bec22c54cdf762c4df5a1a216
Provenance: 0b01470e5f95f0b5fce5c47c9f0702fbe874add2488f029ee9cbcd1e72c20b0b
Harness commit: f4d6b06ddd7ede36a27827d11d653f939a3a2fdb

Selected measurement

Completed: 5 Sep 2026 · 08:01 UTC
Antfly: v0.2.1-rc.3 · 4 September 2026 · 03:12 UTC
Runtime: 1m 17s
Platform: darwin · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Measurement group

complete

Generation

Three fresh Antfly lifecycles. Reference providers: 2026-08-13, not rerun.

Generation result

Antfly v0.2.1-rc.3 · bb8a284d

Model	Variant	Provider	p95 ms	Throughput ops/s	Quality	Peak memory MB	Valid / total
google/gemma-4-E4B-it-qat-q4_0-gguf	QAT q4_0	antfly	837.2	1.22	1.000 pass	6,129.6	3/3
ggml-org/gemma-4-E4B-it-GGUF	Q4_0	llama.cpp	1,809.9	0.56	1.000 pass	7,795.5	3/3
ggml-org/gemma-4-E4B-it-GGUF	Q4_0	ollama	995.2	1.02	1.000 pass	11,459.9	3/3
ggml-org/gemma-4-E4B-it-GGUF	Q4_0	vllm-metal	801.8	1.26	1.000 pass	26,764.0	3/3
google/gemma-4-E4B-it-qat-q4_0-gguf	QAT q4_0	llama.cpp	1,870.7	0.56	1.000 pass	7,974.5	3/3
google/gemma-4-E4B-it-qat-q4_0-gguf	QAT q4_0	ollama	913.6	1.13	1.000 pass	7,746.1	3/3
google/gemma-4-E4B-it-qat-q4_0-gguf	QAT q4_0	vllm-metal	1,082.2	0.93	1.000 pass	29,728.4	3/3
unsloth/Qwen3-1.7B-GGUF	Q4_K_M	llama.cpp	897.7	1.14	1.000 pass	5,940.5	3/3
unsloth/Qwen3-1.7B-GGUF	Q4_K_M	ollama	412.1	2.55	1.000 pass	5,413.5	3/3
unsloth/Qwen3-1.7B-GGUF	Q4_K_M	vllm-metal	318.5	3.16	1.000 pass	27,087.0	3/3

Throughput

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · google/gemma-4-E4B-it-qat-q4_0-gguf · three fresh lifecycles · Higher is better

Peak memory

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · google/gemma-4-E4B-it-qat-q4_0-gguf · three fresh lifecycles · Lower is better

Measurement group

complete

Dense Embedding

Three fresh Antfly lifecycles. Reference providers: 2026-08-13, not rerun.

Dense Embedding result

Antfly v0.2.1-rc.3 · bb8a284d

Model	Variant	Provider	p95 ms	Throughput ops/s	Quality	Peak memory MB	Valid / total
BAAI/bge-small-en-v1.5	f32	antfly	130.6	8.26	0.251 cosine	863.0	3/3
BAAI/bge-small-en-v1.5	f32	onnxruntime	13.4	80.00	0.207 cosine	1,074.0	3/3
BAAI/bge-small-en-v1.5	f32	sentence-transformers	8.8	141.59	0.207 cosine	1,359.8	3/3
BAAI/bge-large-en-v1.5	f32	onnxruntime	58.5	18.56	0.192 cosine	3,615.9	3/3
BAAI/bge-large-en-v1.5	f32	sentence-transformers	20.9	64.92	0.192 cosine	2,408.8	3/3
mixedbread-ai/mxbai-embed-large-v1	f32	onnxruntime	58.6	18.69	0.271 cosine	3,614.3	3/3
mixedbread-ai/mxbai-embed-large-v1	f32	sentence-transformers	20.2	65.97	0.271 cosine	2,761.1	3/3

Throughput

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · BAAI/bge-small-en-v1.5 · three fresh lifecycles · Higher is better

Peak memory

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · BAAI/bge-small-en-v1.5 · three fresh lifecycles · Lower is better

Measurement group

complete

Sparse Embedding

Three fresh Antfly lifecycles. Reference providers: 2026-08-13, not rerun.

Sparse Embedding result

Antfly v0.2.1-rc.3 · bb8a284d

Model	Variant	Provider	p95 ms	Throughput ops/s	Quality	Peak memory MB	Valid / total
sparse-encoder-testing/splade-bert-tiny-nq-onnx	onnx	antfly	12.6	85.87	204.000 entries	402.3	3/3
sparse-encoder-testing/splade-bert-tiny-nq-onnx	onnx	onnxruntime	4.4	253.38	334.000 entries	659.0	3/3
sparse-encoder-testing/splade-bert-tiny-nq-onnx	onnx	sentence-transformers	10.5	130.63	334.000 entries	1,337.5	3/3

Throughput

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · sparse-encoder-testing/splade-bert-tiny-nq-onnx · three fresh lifecycles · Higher is better

Peak memory

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · sparse-encoder-testing/splade-bert-tiny-nq-onnx · three fresh lifecycles · Lower is better

Measurement group

complete

Reranking

Three fresh Antfly lifecycles. Reference providers: 2026-08-13, not rerun.

Reranking result

Antfly v0.2.1-rc.3 · bb8a284d

Model	Variant	Provider	p95 ms	Throughput ops/s	Quality	Peak memory MB	Valid / total
mixedbread-ai/mxbai-rerank-base-v1	f32	antfly	110.6	10.52	1.000 pass	1,899.2	3/3
mixedbread-ai/mxbai-rerank-base-v1	f32	onnxruntime	52.5	19.39	1.000 pass	4,998.0	3/3
mixedbread-ai/mxbai-rerank-base-v1	f32	sentence-transformers	16.7	91.24	1.000 pass	1,915.9	3/3
cross-encoder/ms-marco-MiniLM-L6-v2	f32	onnxruntime	10.5	102.11	1.000 pass	1,006.7	3/3
cross-encoder/ms-marco-MiniLM-L6-v2	f32	sentence-transformers	6.8	199.59	1.000 pass	929.7	3/3

Throughput

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · mixedbread-ai/mxbai-rerank-base-v1 · three fresh lifecycles · Higher is better

Peak memory

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · mixedbread-ai/mxbai-rerank-base-v1 · three fresh lifecycles · Lower is better

Measurement group

complete

Chunking

Three fresh Antfly lifecycles. Reference providers: 2026-08-13, not rerun.

Chunking result

Antfly v0.2.1-rc.3 · bb8a284d

Model	Variant	Provider	p95 ms	Throughput ops/s	Quality	Peak memory MB	Valid / total
fixed_bert	built-in	antfly	7.5	193.39	3.000 chunks	383.6	3/3
fixed_bert	built-in	tokenizers	0.1	21,789.55	3.000 chunks	215.6	3/3
fixed_bpe	built-in	tokenizers	0.1	23,741.61	3.000 chunks	215.7	3/3
mirth/chonky_mmbert_small_multilingual_1	f32	tokenizers	0.1	28,908.90	3.000 chunks	653.7	3/3

Throughput

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · fixed_bert · three fresh lifecycles · Higher is better

Peak memory

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · fixed_bert · three fresh lifecycles · Lower is better

Measurement group

complete

Extraction

Three fresh Antfly lifecycles. Reference providers: 2026-08-13, not rerun.

Extraction result

Antfly v0.2.1-rc.3 · bb8a284d

Model	Variant	Provider	p95 ms	Throughput ops/s	Quality	Peak memory MB	Valid / total
antflydb/gliner2-base-v1	f32	antfly	37.2	27.48	1.000 recall	1,091.2	3/3
antflydb/gliner2-base-v1	f32	gliner2	29.0	35.48	1.000 recall	1,469.2	3/3

Throughput

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · antflydb/gliner2-base-v1 · three fresh lifecycles · Higher is better

Peak memory

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · antflydb/gliner2-base-v1 · three fresh lifecycles · Lower is better

Measurement group

complete

Transcription

Three fresh Antfly lifecycles. Reference providers: 2026-08-13, not rerun.

Transcription result

Antfly v0.2.1-rc.3 · bb8a284d

Model	Variant	Provider	p95 ms	Throughput ops/s	Quality	Peak memory MB	Valid / total
openai/whisper-tiny	f32	antfly	1,649.6	0.61	1.000 word recall	1,333.9	3/3
openai/whisper-tiny	f32	faster-whisper	—	—	0.600 word recall	—	0/3
openai/whisper-tiny	f32	whisper.cpp	124.0	8.61	0.800 word recall	413.3	3/3

Throughput

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · openai/whisper-tiny · three fresh lifecycles · Higher is better

Peak memory

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · openai/whisper-tiny · three fresh lifecycles · Lower is better

document-ohr-bench

partial

OHR-Bench · controlled extraction

Controlled OHR extraction retrieval over all 8,498 questions in each paired input: Antfly v0.2.1 scored 44.33% mean word-LCS versus 70.44% for matched ground-truth text; 73 of 8,561 retained pages had OCR failures.

Methodology scope · protocol · interpretation

Controlled extraction measurement

This lane compares two document-text inputs under one controlled retrieval protocol: text extracted by the official Antfly v0.2.1 ReleaseFast Darwin ARM64 binary and matched OHR ground-truth text. Both use the same fixed 1,261-document candidate manifest, canonical logical paths, tokenizer/model sources, 1,024-token SimpleNodeParser/SentenceSplitter chunks without overlap, and deterministic UUID5 node IDs. Scores are percentage mean word-level evidence LCS at top-2, averaged across all 8,498 questions and both independent BM25 and exact full-precision BGE-M3 lanes. Every question stays in the denominator; unavailable evidence scores zero. There is no RRF or evidence-type reweighting.

Extraction quality

Antfly loaded all 1,261 PDFs and retained page arrays for all 8,561 pages. Seventy-three page OCR outcomes failed across 35 PDFs (0.85% of pages); these are extraction failures, not PDF or page-load failures, and a failed OCR page can retain native text. Two corpus-only PDFs produced no retrievable chunks. The native structural gate therefore remains failed, while the paired controlled scores remain valid descriptive measurements over the full question denominator.

Interpretation

The controlled Antfly and matched-ground-truth rows are directly comparable only to each other. This is not an exact reproduction of the published OHR ranking: the fixed corpus excludes one published ground-truth-only distractor, canonical paths and UUID5 IDs remove filesystem and UUID4 variation, and 42 strict filename-mismatch QA rows remain zero rather than receiving alias repair. Published rows retain their upstream labels and values as a visibly separate reference group. Native Antfly analyzer and BGE-small retrieval metrics are separate diagnostics, not substitutes for the controlled scores. Concurrent workloads make retained timing non-comparable.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: document-ohr-bench
Domain: document/raw-pdf-retrieval
Source: https://github.com/opendatalab/OHR-Bench
Known Antfly versions: v0.2.*
Enabled: yes

Benchmark parameters

{"controlled_measurement":{"candidate_documents":1261,"chunks":27592,"failures_kept_in_denominator":true,"lane_scores_per_input":16996,"metric":"mean word-level evidence LCS at top-2","questions":8498,"retained_pages":8561},"extraction_quality":{"loaded_pdfs":1261,"ocr_attempt_failure_rate":0.04694533762057878,"ocr_attempted_pages":1555,"ocr_failed_documents":35,"ocr_failed_pages":73,"ocr_failed_rate_all_pages":0.00852704123350076,"pages_without_ocr_failure":8488,"retained_pages":8561,"status":"failed","zero_chunk_documents":2},"native_retrieval_diagnostic":{"classification":"separate Antfly analyzer and BGE-small diagnostic; not a controlled score","lanes":{"dense":{"empty_queries":0,"mean_latency_seconds":0.036739,"questions":8498,"top1_mean_lcs":0.262424,"top1_page_recall":0.454931,"top1_questions":8498,"top2_mean_lcs":0.341372,"top2_page_recall":0.566016,"top2_questions":8498,"top5_mean_lcs":0.413611,"top5_page_recall":0.667804,"top5_questions":8498},"hybrid":{"empty_queries":0,"mean_latency_seconds":0.001878,"questions":8498,"top1_mean_lcs":0.302222,"top1_page_recall":0.50153,"top1_questions":8498,"top2_mean_lcs":0.383135,"top2_page_recall":0.607908,"top2_questions":8498,"top5_mean_lcs":0.454335,"top5_page_recall":0.701459,"top5_questions":8498},"lexical":{"empty_queries":948,"mean_latency_seconds":0.001371,"questions":8498,"top1_mean_lcs":0.317588,"top1_page_recall":0.501059,"top1_questions":8498,"top2_mean_lcs":0.386779,"top2_page_recall":0.583549,"top2_questions":8498,"top5_mean_lcs":0.446812,"top5_page_recall":0.659096,"top5_questions":8498}},"missing_provenance":0,"quality_status":"passed","query_errors":0,"structural_status":"failed"},"paired_validation":{"official-antfly":{"lane_scores":16996,"questions":8498,"recomputed_mean":0.44326071858099025,"unique_questions":8498,"verified_domain_artifacts":49},"official-gt":{"lane_scores":16996,"questions":8498,"recomputed_mean":0.7044283388810646,"unique_questions":8498,"verified_domain_artifacts":49},"paired_controls":{"candidate_documents":1261,"identical_candidate_names_and_logical_paths":true,"identical_protocol_environment_model_sources_tokenizers":true,"identical_qa_order":true,"native_declared_failure_documents":35}},"protocol_controls":{"canonical_logical_paths":"data/retrieval_base/evaluation","chunk_overlap":0,"chunk_size":1024,"chunker":"llama_index.node_parser.SimpleNodeParser/SentenceSplitter","deterministic_node_ids":"UUID5(NAMESPACE_URL, logical_file_path + NUL + zero_based_page_idx + NUL + chunk_ordinal); document ordinal=-1","embedding_model":"BAAI/bge-m3","embedding_revision":"5617a9f61b028005a4858fdac845db406aefb181","fixed_corpus_difference":"one published GT-only distractor excluded","published_ranking_claim":false,"retrieval_lanes":["bm25","dense_bge_m3"],"strict_filename_mismatch_qa_rows":42,"top_k":2},"timing":{"comparable":false,"concurrent_workloads":true,"native_setup_wall_seconds":11737.516}}

Retrieval systems

Antfly extraction · BM25 controlled top-2 word-LCS 45.19% mean 8,498 queries
Antfly extraction · BGE-M3 dense controlled top-2 word-LCS 43.46% mean 8,498 queries
Matched ground truth · BM25 controlled top-2 word-LCS 71.34% mean 8,498 queries
Matched ground truth · BGE-M3 dense controlled top-2 word-LCS 69.54% mean 8,498 queries

Published comparison sources

Published OHR evaluation table Upstream reference values; not rerun in the controlled pair Different corpus and identity controls; no ranking claim Source

Peer versions

Peer versions were not recorded in the published result fields.

Evidence digests

Receipt: b749fd8d782fdd7b4adddd679f880ba465b41b1c203a48088f8f252043fd89b2
Aggregate: a47315641ace8ffd8d415fcfed93e11a6c9797300f4461c6bd577a25a804c435
Provenance: f4d505e6547ba01e8d779919b3c356bcbb6b0ae58186c30c3841e4b29d9cecfe
Harness commit: f7c4024229d4f597430f2389950961638a8116ca

Selected partial evidence

Completed: 9 Sep 2026 · 20:10 UTC
Antfly: v0.2.1
Runtime: —
Platform: darwin · arm64
Machine: Apple M5 Pro
Build: ReleaseFast

Overall duration is omitted because controlled and diagnostic workloads overlapped; completion marks the evidence seal.

Controlled extraction scores · published references kept separate

Antfly v0.2.1 · e5261e9e

Evidence group	Document source	TXT	TAB	FOR	CHA	RO	MUL	ALL %	OCR-failed pages
Controlled paired run	Antfly v0.2.1 extraction	58.79	45.24	36.90	23.44	6.89	40.88	44.33	73 / 8,561 (0.85%)
Controlled paired run	Matched OHR ground truth	81.75	70.10	75.91	68.24	10.05	62.68	70.44	—
Published upstream table	Ground Truth	81.6	69.8	75.2	70.3	9.8	—	70.4	—
Published upstream table	MinerU 0.9.3	68.1	48.6	51.3	16.5	5.9	—	50.5	—
Published upstream table	Marker 1.2.3	75.5	58.2	55.5	20.0	5.9	—	57.0	—
Published upstream table	Azure Document Intelligence	78.0	59.4	55.2	45.2	5.8	—	60.6	—
Published upstream table	GOT	62.5	41.1	49.0	17.4	3.7	—	45.8	—
Published upstream table	Nougat	59.5	32.8	44.3	11.3	4.4	—	41.2	—
Published upstream table	Qwen2.5-VL-72B	75.1	60.0	60.0	38.2	5.3	—	59.6	—
Published upstream table	InternVL2.5-78B	68.6	57.9	55.6	45.1	2.7	—	56.2	—
Published upstream table	olmOCR-7B-0225-preview	72.5	58.4	55.4	24.8	5.0	—	56.6	—
Published upstream table	MonkeyOCR	74.6	56.5	55.5	16.5	5.7	—	55.9	—
Published upstream table	Nanonets-OCR-s	71.8	59.8	57.4	43.7	4.4	—	58.3	—

Extraction quality and corpus retention

Antfly v0.2.1 · e5261e9e

Outcome	Valid / total	Observed boundary	Failure rate %
PDF loading	1,261 / 1,261	0 load failures	0.00%
Page retention	8,561 / 8,561	0 dropped pages	0.00%
Pages without OCR failure	8,488 / 8,561	73 failures across 35 PDFs	0.85%
Retrievable chunks	1,259 / 1,261	2 zero-chunk PDFs	0.16%

1 of 3 lanes measured

CRAG

Retrieval, ranking, and evaluation lanes over the CRAG corpus and query set.

fulltext-crag-footprint

complete

Full-text search

Full-text query behavior and quality across increasing CRAG corpus sizes, paired with swap-backed serving demand and complete post-stop database volume.

Methodology scope · protocol · interpretation

CRAG full-text search

Scope

This lane compares Antfly, Elasticsearch, and Quickwit as full-text retrieval services over the same CRAG Task 1/2 corpus and query sample. At 2,000, 5,000, 9,000, and 13,530 documents it measures cache-excluded working set, cache-inclusive memory, final complete database volume, query p95, QPS, and normalized gold-answer evidence in the top one and top five results.

The main report repeats the honed publication charts for working set, final database volume, and query p95 by corpus size. The tables retain QPS and quality beside those plots. This is a full-text search comparison, not merely a footprint measurement.

Publication protocol

Run every engine in a Linux cgroup v2 container on the shared Circus Linux/arm64 lane.
Use the same immutable CRAG corpus and query set for all engines.
Give Elasticsearch a fixed 1 GiB heap and record that setting.
Run three fresh alternating lifecycles, rather than reusing an index or container between repetitions.
For each lifecycle, run one deterministic 200-query sample at concurrency 1 after ten warmup queries; require zero query errors.
Use product-default full-text analyzers and resolve returned IDs through the same canonical CRAG document map before calculating top-one and top-five gold-answer evidence.
Treat sampled cgroup memory.current as cache-inclusive memory and anon + shmem as the cache-excluded working-set comparison.
Give every engine one newly created, run-labeled Docker local volume at its complete persistence root: /data, /usr/share/elasticsearch/data, or /quickwit/qwdata. The same digest-pinned Alpine probe measures each whole volume on the shared Linux Docker engine; APFS bind mounts are ineligible.
Give every engine the same fixed 30-second post-workload persistence window, then capture allocated and apparent integer bytes once at post_workload. Also capture once at empty and ready, then at the post-stop final barrier. empty permits root directory-block overhead but no entries. Verify graceful stop before the headline final capture; neither the delay nor qualification depends on an engine’s observed bytes.
Publish final allocated bytes as the arithmetic mean, every value, and the full range of the three independent construction lifecycles. Retain apparent bytes, lifecycle samples, per-volume manifests, and engine index APIs only as diagnostics. The legacy index_disk_mb field is not comparable.
Require storage.json and its validation receipt, which ties the measurement to the sampler hash, probe digest, declared scope, lifecycle barriers, environment identity, and fresh or materialized cell sums.
Require the quiet-host gate for latency publication. Memory and storage remain valid only when all engine cells passed their lifecycle and cgroup checks.

The v0.2.0 honed page describes the host as Linux/aarch64 containers under Docker Desktop on Apple Silicon. It does not describe this as bare-metal Linux.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: fulltext-crag-footprint
Domain: full-text/retrieval
Source: https://github.com/facebookresearch/CRAG
Known Antfly versions: v0.1.3, v0.2.*
Expected duration: 75 min
Enabled: yes

Benchmark parameters

{"document_counts":[2000,5000,9000,13530],"trial_count":3}

Trial variation

[{"document_count":2000,"engine":"antfly","ranges":{"demand_working_set":{"maximum":182.837248,"mean":179.8554,"minimum":167.006208,"unit":"MB"},"final_database_volume":{"maximum":28.07808,"mean":28.07808,"minimum":28.07808,"unit":"MB"},"query_p95":{"maximum":0.7512,"mean":0.7486,"minimum":0.6019,"unit":"ms"}}},{"document_count":5000,"engine":"antfly","ranges":{"demand_working_set":{"maximum":232.620032,"mean":203.8907,"minimum":194.62144,"unit":"MB"},"final_database_volume":{"maximum":77.807616,"mean":77.80352,"minimum":77.799424,"unit":"MB"},"query_p95":{"maximum":0.9326,"mean":0.7722,"minimum":0.7256,"unit":"ms"}}},{"document_count":9000,"engine":"antfly","ranges":{"demand_working_set":{"maximum":348.274688,"mean":327.2827,"minimum":308.277248,"unit":"MB"},"final_database_volume":{"maximum":116.81792,"mean":116.81792,"minimum":116.81792,"unit":"MB"},"query_p95":{"maximum":1.0176,"mean":0.9798,"minimum":0.831,"unit":"ms"}}},{"document_count":13530,"engine":"antfly","ranges":{"demand_working_set":{"maximum":463.740928,"mean":429.3673,"minimum":375.11168,"unit":"MB"},"final_database_volume":{"maximum":191.320064,"mean":178.120021,"minimum":171.52,"unit":"MB"},"query_p95":{"maximum":1.0528,"mean":0.9679,"minimum":0.8714,"unit":"ms"}}},{"document_count":2000,"engine":"elasticsearch","ranges":{"demand_working_set":{"maximum":1563.168768,"mean":1561.5468,"minimum":1550.176256,"unit":"MB"},"final_database_volume":{"maximum":28.176384,"mean":28.176384,"minimum":28.176384,"unit":"MB"},"query_p95":{"maximum":3.1022,"mean":3.0962,"minimum":2.9788,"unit":"ms"}}},{"document_count":2000,"engine":"quickwit","ranges":{"demand_working_set":{"maximum":342.7328,"mean":326.5659,"minimum":320.233472,"unit":"MB"},"final_database_volume":{"maximum":62.17728,"mean":62.17728,"minimum":62.17728,"unit":"MB"},"query_p95":{"maximum":2.4123,"mean":2.3783,"minimum":2.1956,"unit":"ms"}}},{"document_count":5000,"engine":"elasticsearch","ranges":{"demand_working_set":{"maximum":1592.815616,"mean":1578.7663,"minimum":1568.456704,"unit":"MB"},"final_database_volume":{"maximum":68.071424,"mean":68.065963,"minimum":68.05504,"unit":"MB"},"query_p95":{"maximum":3.1904,"mean":3.1856,"minimum":3.0442,"unit":"ms"}}},{"document_count":5000,"engine":"quickwit","ranges":{"demand_working_set":{"maximum":437.26848,"mean":431.4522,"minimum":428.675072,"unit":"MB"},"final_database_volume":{"maximum":153.464832,"mean":153.464832,"minimum":153.464832,"unit":"MB"},"query_p95":{"maximum":2.8585,"mean":2.7023,"minimum":2.674,"unit":"ms"}}},{"document_count":9000,"engine":"elasticsearch","ranges":{"demand_working_set":{"maximum":1625.956352,"mean":1603.6454,"minimum":1601.2288,"unit":"MB"},"final_database_volume":{"maximum":121.38496,"mean":121.379499,"minimum":121.368576,"unit":"MB"},"query_p95":{"maximum":3.3096,"mean":3.1342,"minimum":3.1236,"unit":"ms"}}},{"document_count":9000,"engine":"quickwit","ranges":{"demand_working_set":{"maximum":590.016512,"mean":575.1603,"minimum":566.632448,"unit":"MB"},"final_database_volume":{"maximum":140.92288,"mean":140.92288,"minimum":140.92288,"unit":"MB"},"query_p95":{"maximum":3.3839,"mean":3.3089,"minimum":2.9987,"unit":"ms"}}},{"document_count":13530,"engine":"elasticsearch","ranges":{"demand_working_set":{"maximum":1637.146624,"mean":1634.689,"minimum":1626.558464,"unit":"MB"},"final_database_volume":{"maximum":181.444608,"mean":181.444608,"minimum":181.444608,"unit":"MB"},"query_p95":{"maximum":3.4245,"mean":3.2994,"minimum":3.2854,"unit":"ms"}}},{"document_count":13530,"engine":"quickwit","ranges":{"demand_working_set":{"maximum":701.820928,"mean":684.7078,"minimum":650.620928,"unit":"MB"},"final_database_volume":{"maximum":278.646784,"mean":278.644053,"minimum":278.642688,"unit":"MB"},"query_p95":{"maximum":3.9363,"mean":3.7102,"minimum":3.7017,"unit":"ms"}}}]

Peer versions

Peer versions were not recorded in the published result fields.

Evidence digests

Receipt: 448ebca5a6af2d2f24c1798a0445ea03a8d7dbf9d544bd19772e53efbf4a06dd
Aggregate: 204890e6d564ab1b728f0b52c67dc19a771b2c5b7e9dcc19930fdc0a2bf1e692
Provenance: 48fdc7b3bd7bb17cbf3b30983f7fb6886531f931e0586c58153530f86fd549d3
Harness commit: 059cc9cfa10a2e76d7d4e7c518044c9327215473

Selected measurement

Completed: 22 Aug 2026 · 13:40 UTC
Antfly: 46b702a8 · 22 August 2026 · 02:16 UTC
Runtime: 28m 51s
Platform: linux · arm64
Machine: Docker Desktop VM on Apple M4 Max · 10 CPU · 27.3 GB
Build: ReleaseFast · Zig compiler version not captured

Query p95

Antfly development build (46b702a8) · Platform: linux-arm64 · Processor: Docker Desktop VM on Apple M4 Max · 2,000–13,530 documents · 3 trials · Lower is better

Demand working set

Antfly development build (46b702a8) · Platform: linux-arm64 · Processor: Docker Desktop VM on Apple M4 Max · 2,000–13,530 documents · 3 trials · Lower is better

Final database volume

Antfly development build (46b702a8) · Platform: linux-arm64 · Processor: Docker Desktop VM on Apple M4 Max · 2,000–13,530 documents · 3 trials · Lower is better

Resource footprint

Antfly development build · 46b702a8

Engine	Documents	Demand working set MB	Final database volume MB	Trials
antfly	2,000	179.9 MB	28.1 MB	3
antfly	5,000	203.9 MB	77.8 MB	3
antfly	9,000	327.3 MB	116.8 MB	3
antfly	13,530	429.4 MB	178.1 MB	3
elasticsearch	2,000	1,561.5 MB	28.2 MB	3
quickwit	2,000	326.6 MB	62.2 MB	3
elasticsearch	5,000	1,578.8 MB	68.1 MB	3
quickwit	5,000	431.5 MB	153.5 MB	3
elasticsearch	9,000	1,603.6 MB	121.4 MB	3
quickwit	9,000	575.2 MB	140.9 MB	3
elasticsearch	13,530	1,634.7 MB	181.4 MB	3
quickwit	13,530	684.7 MB	278.6 MB	3

Query behavior and ranking quality

Antfly development build · 46b702a8

Engine	Documents	QPS	p95 ms	Top-1	Top-5
antfly	2,000	1,824.3	0.75	0.220	0.295
antfly	5,000	1,877.6	0.77	0.230	0.290
antfly	9,000	1,441.6	0.98	0.230	0.285
antfly	13,530	1,578.7	0.97	0.235	0.290
elasticsearch	2,000	486.9	3.10	0.200	0.285
quickwit	2,000	525.1	2.38	0.215	0.290
elasticsearch	5,000	488.5	3.19	0.210	0.280
quickwit	5,000	444.0	2.70	0.215	0.295
elasticsearch	9,000	465.0	3.13	0.210	0.285
quickwit	9,000	374.5	3.31	0.220	0.295
elasticsearch	13,530	460.2	3.30	0.215	0.280
quickwit	13,530	313.7	3.71	0.220	0.295

rag-crag

missing

Dense retrieval diagnostic

Controlled dense-retrieval diagnostics over the CRAG corpus and query set.

Methodology scope · protocol · interpretation

CRAG dense retrieval diagnostic

What this lane measures

This is a retrieval-only diagnostic over the official CRAG Task 1/2 v4 development data. It compares how six vector databases retrieve answer-bearing passages from the same corpus. It is not an official CRAG Task 1/2 score: it stops before answer generation and does not run the official CRAG judge.

Upstream CRAG evaluates generated answers to questions whose relevant context may change over time. The full upstream workflow supplies retrieved context to an answer model and evaluates the answer. This Circus lane uses CRAG only as a fixed real-world question and web-page source so that database retrieval can be measured separately from model quality, provider latency, and judge behavior.

Retrieval protocol

Dataset: official Task 1/2 v4 development split, 2,706 questions and 13,530 provided web-result pages.
Dataset SHA-256: afa29f2b3facfb5d15aa9cded00d5ec90ff76f3e67279e7b99cfe86659a641ca.
Documents: normalize each source page, cap it at 20,000 characters, then form deterministic 384-token passages with 64-token overlap.
Embeddings: normalized 384-dimensional BAAI/bge-small-en-v1.5 vectors, computed once and loaded unchanged into every engine.
Search: identical query vectors, fixed query order, cosine distance, and the top five complete passages.
Engines: Antfly, Milvus, Chroma, pgvector, Weaviate, and Elasticsearch.
Evidence: service version, image identity, effective index settings, subject version and SHA-256, and per-query retrieval rows are retained before the aggregate is accepted.

The gauntlet adds retrieval-only lexical, hybrid, and local agentic/KG rows. Those rows are diagnostics, not substitutes for the six-engine dense cohort. Paid answer generation and judging require the separately guarded full CRAG command and are not part of this Circus benchmark lane.

Metrics and publication status

The harness records retrieval latency and whether any normalized gold-answer string appears in the top-one or top-five retrieved context. These are local retrieval sanity metrics, not the official CRAG judge score.

This lane is excluded from the honed publication profile. Its current adapters use unequal client transports: Antfly and Elasticsearch open a new HTTP connection and serialize JSON inside each timed request, while other engines use persistent native clients. The ANN settings also were not calibrated to a common recall floor. Those differences confound both latency and hit-at-five rankings, so the Circus profile retains the lane only as a diagnostic and must not present a cross-engine leaderboard from it.

Evidence status availability · expected contract

Benchmark metadata

Benchmark ID: rag-crag
Domain: retrieval/dense-vector-diagnostic
Source: https://github.com/facebookresearch/CRAG
Known Antfly versions: v0.2.*
Enabled: yes

Why this lane has no selected measurement

No reviewed benchmark result is selected for this subject.

Expected: Reviewed aggregate with a validation receipt
Observed: No result selected for this subject

iii

ragas-crag-eval

missing

RAGAS evaluation

RAG answer and retrieval quality measured with the RAGAS evaluation surface.

Methodology scope · protocol · interpretation

RAGAS CRAG Evaluation Methodology

Scope

This benchmark evaluates the CRAG RAG artifacts generated by the rag-crag benchmark entry. It does not run a separate retrieval stack; it consumes the saved CRAG retrieval and answer JSONL files so the RAGAS row describes the same RAG behavior shown in the CRAG table.

Current Metrics

The initial adapter reports RAGAS-shaped proxy metrics from CRAG artifacts:

context_recall_proxy: whether the gold answer appears in top-k context
context_precision_proxy: whether the gold answer appears in top-one context
answer_correctness_proxy: whether the generated answer contains the gold answer
missing_rate: how often the answer generator returned no answer or unknown

If the ragas Python package is installed, the adapter records that fact, but the current row still uses CRAG artifact proxies. A follow-up should add the true RAGAS metric calls after the exact LLM and embedding provider choices are settled.

Inputs

Retrieval artifacts: rag-crag/*-retrieval.jsonl
Answer artifacts: rag-crag/*-answers.jsonl
Summary files: rag-crag/retrieval-summary.json and rag-crag/answer-summary.json

The row is provisional until true RAGAS package metrics are enabled.

Evidence status availability · expected contract

Benchmark metadata

Benchmark ID: ragas-crag-eval
Domain: rag/orchestration
Source: https://github.com/vibrantlabsai/ragas
Known Antfly versions: v0.2.*
Enabled: yes

Why this lane has no selected measurement

No reviewed benchmark result is selected for this subject.

Expected: Reviewed aggregate with a validation receipt
Observed: No result selected for this subject

VII

fulltext-miracl-scale

partial

MIRACL full-text scale

Retained September 2 Antfly v0.2.1-rc2 MIRACL evidence, using 799 public development queries and 8,350 human relevance judgments.

Methodology scope · protocol · interpretation

Full-text MIRACL scale methodology

Scope

fulltext-miracl-scale measures full-text operational cost with retrieval-quality guardrails as a judged English passage field grows. Antfly, Elasticsearch, Quickwit, and PostgreSQL built-in full-text search index identical nested fixtures and answer the same MIRACL English development queries. The lane reports complete service memory demand, final allocated database-volume bytes, index duration, query p95/QPS, and judged ranking metrics.

This lane supplies million-scale lexical operational evidence. Search Benchmark Game owns query-class throughput, BEIR owns native-hybrid uplift, and STaRK owns structured retrieval. No service-count, round-trip consolidation, or official MIRACL leaderboard claim follows from this lane.

Source and license

The corpus is the English portion of MIRACL v1.0: 32,893,221 passages from 5,758,285 English Wikipedia articles. The public development panel contains 799 queries and 8,350 human positive and negative judgments. Corpus repository revision d921ec7e349ce0d28daf30b2da9da5ee698bef0d and judgment repository revision 5be20db9509754dadad47689368639fcec739c00 are immutable cache identities. Every corpus shard is pinned by its Hugging Face LFS SHA-256; topics and qrels are pinned by observed SHA-256.

The MIRACL dataset cards declare Apache-2.0. The corpus is derived from English Wikipedia, so applicable Wikipedia attribution and share-alike obligations are retained rather than treating the text as newly permissive content.

Citation:

Xinyu Zhang, Nandan Thakur, Odunayo Ogundepo, Ehsan Kamalloo, David Alfonso-Hermelo, Xiaoguang Li, Qun Liu, Mehdi Rezagholizadeh, and Jimmy Lin. “MIRACL: A Multilingual Retrieval Dataset Covering 18 Diverse Languages.” Transactions of the Association for Computational Linguistics 11, 2023. DOI 10.1162/tacl_a_00595.

Deterministic nested fixtures

Each source passage becomes one canonical UTF-8 JSONL record with MIRACL docid as id and title + U+000A + text as the searchable text. Source strings are not normalized, truncated, or analyzer-normalized.

Every document appearing in a development qrel is placed first, ordered by UTF-8 document ID. Natural distractors are ordered by SHA-256 of the UTF-8 document ID. The implementation scans every pinned corpus shard, retains low SHA-256 prefix buckets, externally sorts only the retained candidate set under LC_ALL=C, and writes exact nested prefixes of 250,000, 1,000,000, 2,000,000, 3,000,000, and 5,000,000 passages. Every judged document must occur in every prefix. Selection does not inspect relevance grade.

Queries are exact MIRACL development topic text in UTF-8 query-ID order. Qrels are canonical four-column TREC rows in query-ID/document-ID order. Preparation rejects duplicate judgments, missing positive queries, missing judged documents, malformed rows, source count drift, and digest drift. preparation-receipt.json binds every source asset, full-corpus canonical digest, prefix identity, query order, qrels, grade histogram, judged-document counts, and selection algorithm.

Engine and query protocol

All engines receive one text field with product-default English lexical analysis. Antfly retains bounded ingest retries, a 900-second request timeout required by observed 5M-pass compaction stalls, and its searchable-readiness gate. Elasticsearch uses one primary shard, no replicas, a 1 GiB heap, refresh, and force merge. Quickwit uses its default tokenizer with positions and field norms; startup ingest retries tolerate the temporary no-shard gate, and publication waits up to 900 seconds for the exact indexed count. PostgreSQL 16 uses a generated English tsvector, a GIN index, and ts_rank_cd, with otherwise default server settings.

The runner streams the declared fixture and requires the indexed count to match. The first ten ordered queries are warmups. The measured pass includes all 799 queries once at concurrency one with top_k=100. Per-query latency spans request dispatch through complete response decoding; QPS is query count divided by measured wall time. Raw evidence contains only query ID, one-based ranked IDs, latency, and normalized error status.

Quality metrics

MIRACL English dev judgments are binary. The lane macro-averages:

nDCG@10;
MRR@10;
Recall@100;
Judged@100, the fraction of returned unique IDs having either a positive or negative human judgment.

MIRACL uses pooled judgments: an unjudged passage is not proven irrelevant. Judged@100 exposes assessment coverage, while nDCG, MRR, and Recall act as consistent cross-engine guardrails. Verification recomputes every metric from retained ranked IDs and rejects request errors, unknown IDs, duplicates, more than 100 hits, query-order drift, and summary disagreement.

Resource lifecycle and failures

The canonical publication cohort is four engines by four common prefix sizes (250K, 1M, 2M, and 3M) by three fresh trials. The retained 5M fixture is a diagnostic boundary: exploratory evidence showed PostgreSQL ranking would consume roughly another half day and Antfly entered sustained full-text merge backpressure, while Elasticsearch and Quickwit completed. Odd canonical trials run Antfly, Elasticsearch, Quickwit, PostgreSQL; even trials reverse the order. Cgroup v2 sampling begins before indexing and continues through all queries at 300 ms. Every engine is measured as one complete service container, and PostgreSQL shmem is included. Headline demand is peak concurrent anon + shmem; memory.current and kernel peaks remain diagnostics.

Fresh labeled Docker volumes capture empty, ready, post_workload, and stopped final barriers. post_workload follows a fixed 30-second settlement. Final allocated and apparent bytes use arithmetic mean plus every value/range; demand, index duration, p95, QPS, and judged metrics use median plus every value/range.

Every planned cell writes normalized status and a digest-bound receipt. All cells are attempted once. Aggregate status is ok for complete success, failed for a repeated uniform terminal gate across a complete engine/size group, and partial for every other fully accounted mix. Unaccounted cells invalidate finalization.

Circus packages presentation-neutral aggregate, source receipt, summary, methodology, input manifest, and preparation receipt through evidence_handoff.py; the site repository owns evidence selection and presentation.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: fulltext-miracl-scale
Domain: full-text/retrieval
Source: https://huggingface.co/datasets/miracl
Known Antfly versions: v0.2.1-rc2
Enabled: yes

Benchmark parameters

{"common_complete_through_passages":3000000,"corpus_passages":32893221,"corpus_sizes":[250000,1000000,2000000,3000000,5000000],"dataset":"MIRACL v1.0 English development split","evidence_class":"1-trial descriptive scaling evidence","fresh_lifecycles_per_point":1,"judgments":8350,"memory_metric":"cgroup v2 anon + shmem","omissions":[{"engine":"postgresql","passages":5000000,"reason":"The complete 3M query pass took 4.45 hours at 0.0499 QPS. A full 5M pass was projected to consume substantially more than the remaining useful overnight window; the query panel was not narrowed and no timeout value was presented as latency."}],"queries":799,"storage_metric":"final allocated database-volume bytes"}

Peer versions

Peer versions were not recorded in the published result fields.

Evidence digests

Receipt: 0e9849866c690064980eef699805cb5123c4b19ea3979f02fd20995036488c95
Aggregate: 4069aa330155db2450d71df331764658fb9e7bdacfd3c4c8962e5c0fb105e162
Provenance: b89529140dde5c5556f0e7c32839ec62b59266fcde0e20a7d664c52636aef0ee
Harness commit: d400ffc1eb4e70beca97983aaec2abeccba9c7a3

Selected partial evidence

Completed: 2 Sep 2026 · 18:00 UTC
Antfly: v0.2.1-rc2 · 30 August 2026 · 23:16 UTC
Runtime: 12h 11m
Platform: linux · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Query p95

Antfly v0.2.1-rc2 (4be5a0e9, ReleaseFast) · Linux/arm64 containers on Apple M4 Max · MIRACL English dev · 1 fresh lifecycles planned per point · Log scale · lower is better

Demand working set

Antfly v0.2.1-rc2 (4be5a0e9, ReleaseFast) · Linux/arm64 containers on Apple M4 Max · MIRACL English dev · 1 fresh lifecycles planned per point · Lower is better

Final database volume

Antfly v0.2.1-rc2 (4be5a0e9, ReleaseFast) · Linux/arm64 containers on Apple M4 Max · MIRACL English dev · 1 fresh lifecycles planned per point · Lower is better

Working set and complete post-stop volume

Antfly v0.2.1-rc2 · 4be5a0e9

Engine	Passages	Demand MB	Cache + memory MB	Final volume MB	Valid / total
Antfly	250,000	469.5 MB	795.9 MB	157.4 MB	1 / 1
Elasticsearch	250,000	1,712.7 MB	2,305.5 MB	123.3 MB	1 / 1
PostgreSQL	250,000	207.6 MB	901.3 MB	665.9 MB	1 / 1
Quickwit	250,000	547.4 MB	767.7 MB	202.7 MB	1 / 1
Antfly	1,000,000	1,811.9 MB	2,669.0 MB	596.3 MB	1 / 1
Elasticsearch	1,000,000	1,801.2 MB	2,886.6 MB	477.4 MB	1 / 1
PostgreSQL	1,000,000	293.1 MB	2,758.3 MB	2,322.6 MB	1 / 1
Quickwit	1,000,000	1,102.4 MB	1,725.0 MB	390.6 MB	1 / 1
Antfly	2,000,000	5,207.8 MB	6,747.4 MB	1,137.8 MB	1 / 1
Elasticsearch	2,000,000	1,881.6 MB	5,001.3 MB	947.0 MB	1 / 1
PostgreSQL	2,000,000	327.0 MB	3,936.5 MB	3,495.2 MB	1 / 1
Quickwit	2,000,000	1,827.8 MB	2,936.2 MB	773.4 MB	1 / 1
Antfly	3,000,000	8,279.2 MB	10,501.1 MB	1,721.4 MB	1 / 1
Elasticsearch	3,000,000	1,880.9 MB	4,903.8 MB	1,416.2 MB	1 / 1
PostgreSQL	3,000,000	321.3 MB	5,114.4 MB	4,645.2 MB	1 / 1
Quickwit	3,000,000	2,210.9 MB	3,818.9 MB	1,029.1 MB	1 / 1
Elasticsearch	5,000,000	1,881.5 MB	7,694.0 MB	2,352.8 MB	1 / 1
Quickwit	5,000,000	2,154.3 MB	4,785.5 MB	2,212.5 MB	1 / 1

Query and judged retrieval evidence

Antfly v0.2.1-rc2 · 4be5a0e9

Engine	Passages	QPS	p95 ms	nDCG@10	Recall@100	Judged@100
Antfly	250,000	788.289	2.28	0.576	0.942	0.098
Elasticsearch	250,000	363.665	3.44	0.552	0.930	0.094
PostgreSQL	250,000	2.719	1,081.78	0.239	0.791	0.083
Quickwit	250,000	47.024	22.80	0.555	0.939	0.095
Antfly	1,000,000	405.904	5.92	0.532	0.928	0.094
Elasticsearch	1,000,000	302.605	4.36	0.493	0.892	0.090
PostgreSQL	1,000,000	0.350	12,385.26	0.143	0.630	0.061
Quickwit	1,000,000	43.014	25.66	0.498	0.903	0.091
Antfly	2,000,000	249.998	10.42	0.459	0.844	0.086
Elasticsearch	2,000,000	258.106	5.62	0.453	0.866	0.087
PostgreSQL	2,000,000	0.091	37,382.05	0.097	0.508	0.048
Quickwit	2,000,000	40.320	27.82	0.458	0.877	0.088
Antfly	3,000,000	182.201	15.01	0.462	0.859	0.087
Elasticsearch	3,000,000	195.861	7.15	0.425	0.849	0.085
PostgreSQL	3,000,000	0.050	61,861.82	0.076	0.432	0.041
Quickwit	3,000,000	38.805	29.29	0.427	0.856	0.086
Elasticsearch	5,000,000	168.856	8.73	0.390	0.825	0.082
Quickwit	5,000,000	27.452	46.30	0.391	0.829	0.083

VIII

deployment-artifacts

complete

Deployment artifacts

Antfly main-09b78df97 stripped ReleaseFast has a 142.2 MB static Linux ARM64 executable and a 63.0 MB operator-created gzip archive. Peer rows retain their original registry metadata.

Methodology scope · protocol · interpretation

Deployment artifacts

This lane establishes packaging and transfer facts for the exact Linux/arm64 artifacts represented by the honed benchmark review. It does not start a database, measure runtime resource use, or assign a composite score.

Cohort and identity

The cohort is Antfly plus the five peers in the honed VectorDBBench publication matrix: Weaviate, pgvector, Chroma, Milvus, and Elasticsearch. Antfly is bound to the exact archive and executable in the honed subject manifest. A published subject resolves its archive through the GitHub Releases API. An operator-built subject instead names its retained local archive explicitly; the collector verifies the file name and SHA-256 before measuring it. Each peer is bound to the exact digest-pinned image reference declared by this lane and uses the same image environment overrides as VectorDBBench.

Every engine/artifact pair is one portable publication-cache cell. A cache hit requires the same subject archive identity or peer image reference, platform, collector protocol, and workload identity. Cache objects retain normalized facts, source metadata, logs, and a lifecycle receipt. Cache identity excludes timing because the lane performs no timed work.

Download payload

Antfly’s download payload is the byte size of the exact Linux/arm64 subject archive. For a published release, the collector requires the GitHub Releases API asset digest to match the archive SHA-256 in the honed subject manifest. For an operator build, it requires an explicit retained archive path and verifies the local file’s name and SHA-256 against the same manifest fields. The result identifies whether the archive came from an official release or an operator build. It separately retains the executable byte size, executable SHA-256, and static-linkage identification from that subject manifest.

A peer’s download payload is the sum of the compressed layer sizes in the one os=linux, architecture=arm64 child selected from docker manifest inspect --verbose. The collector retains the configured index reference, resolved child digest, selected descriptor, config digest, layer count, and selected manifest. Missing or ambiguous platform selection fails the lane.

The image total sums every compressed layer in the selected manifest without credit for layers already cached on an operator’s machine. A machine with shared layers may therefore transfer less. Registry transfer overhead and expanded filesystem size are excluded. This is a reproducible artifact comparison, not an estimate of every installation path.

Deployment vocabulary

“Separately managed prerequisites” means software an operator must install, launch, upgrade, and coordinate separately from the displayed server artifact. None excludes operating-system kernel, storage, and networking. Peer container rows therefore name an OCI-compatible container runtime. Components packaged inside an image, such as Elasticsearch’s JVM or Milvus’s embedded etcd/local-storage topology, are bundle components rather than separately managed prerequisites.

The compact review table describes only the exact artifacts used by the publication matrix. It does not claim that these are the only installation forms supported by each project.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: deployment-artifacts
Domain: deployment/artifacts
Source: https://github.com/antflydb/antfly/releases
Known Antfly versions: v0.1.3, v0.2.*
Expected duration: 2 min
Enabled: yes

Benchmark parameters

{"artifacts":[{"archive_name":"antfly-main-09b78df97-releasefast-linux-arm64.tar.gz","archive_sha256":"48d07c80b7977d8c17ee4ab6bee68100a2c71aefe41e41a92def32985f1c20ce","bundle_components":[],"engine":"antfly","executable_sha256":"6366535c49a75b8c4da691096b0cb7799daa6968f68e5a45377f20e6a321c470","linkage":"static","prerequisites":[]}],"execution_environment":{"container_runtime":"Podman podman version 6.1.1","controller_platform":"darwin-arm64","processor":"Apple M4 Max","service_platform":"linux-arm64","vm_cpus":10,"vm_memory_bytes":29347610624,"vm_memory_gib":27.3},"platform":"linux-arm64"}

Peer versions

Weaviate1.39.2
pgvector0.8.6
Chroma1.5.9
Milvus2.6.22
Elasticsearch9.5.2

Evidence digests

Receipt: a94808d04ac92280a4628b69b9aa2475fd610729c1515c6adbb38b0327756a64
Aggregate: 0d9d8eec8fc01f1273c7b71ca2c21720517782cdc18f49e6f0228a1f4de93877
Provenance: 0d9d8eec8fc01f1273c7b71ca2c21720517782cdc18f49e6f0228a1f4de93877
Harness commit: 82c699bb7a687b65efc691ec329368494ce8499e

Selected measurement

Completed: 6 Oct 2026 · 07:20 UTC
Antfly: main-09b78df97 · 6 October 2026 · 00:55 UTC
Runtime: 0.1s
Platform: linux · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Linux/arm64 deployable artifacts

Antfly main-09b78df97 · 09b78df9

Engine	Deployable form	Artifact origin	Download MB	Executable MB	Status	Source date
antfly	Static executable	operator supplied archive	63.0	142.2	ok	2026-10-06
weaviate	Weaviate server container image	OCI registry manifest	88.2	—	ok	2026-08-31
pgvector	PostgreSQL + pgvector container image	OCI registry manifest	154.1	—	ok	2026-08-31
chroma	Chroma server container image	OCI registry manifest	165.2	—	ok	2026-08-31
milvus	Standalone container image	OCI registry manifest	363.6	—	ok	2026-08-31
elasticsearch	Container image with JVM	OCI registry manifest	758.8	—	ok	2026-08-31

3 of 3 lanes measured

STaRK

Official retrieval quality over textual and relational knowledge bases, with exact candidate, query, metric, and lifecycle provenance.

retrieval-stark-prime

complete

Prime

Antfly v0.2.1-rc.3 completed two fresh 2,801-query lifecycles. Peer database rows retain August 29 observations; published baselines retain their own protocols. Storage is provisional after abnormal shutdowns.

Methodology scope · protocol · interpretation

STaRK-Prime in Antfly Circus

This lane evaluates entity retrieval over the pinned official STaRK-Prime corpus of 129,375 records and the complete official 2801-query test split. Candidate identity uses stable official numeric candidate IDs; quality uses the official STaRK evaluator with official text-embedding-ada-002 vectors. The benchmark definition follows the STaRK paper, arXiv 2504.05478v2.

Terms

Lexical: full-text ranking over serialized entity text.
Dense: nearest-neighbor search over the official embeddings.
RRF: reciprocal-rank fusion of lexical and dense rankings.
Relation-expanded: STaRK’s flattened relation-context serialization.
Recall@20: mean fraction of gold entity IDs returned in the first 20 results.

Container memory

The retained metric is concurrent cgroup-v2 anon plus shmem peak, sampled every 0.2 seconds before readiness through the final query. This cgroup-v2 anon + shmem metric is the same under Docker and Podman; the runtime does not change its memory definition.

Storage observation

Storage covers the whole writable database persistence volume at the empty, ready, post_workload, final barriers. Antfly storage uses Linux-volume schema v2 but remains provisional after abnormal service shutdowns. Archival peers predate the filesystem-identity contract. Retain observations only; no qualified storage headline or cross-engine ratios.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: retrieval-stark-prime
Domain: retrieval/knowledge-base
Source: https://github.com/snap-stanford/stark
Known Antfly versions: v0.2.1-rc.3
Enabled: yes

Benchmark parameters

{"candidate_identity_sha256":"6052523f61b8939595a1c0a98eb951529b7f469585edd0b69c1d706533014e6d","dataset":"snap-stanford/stark","dataset_revision":"88269e23e90587f99476c5dd74e235a0877e69be","queries":2801,"records":129375,"vector_dimensions":1536,"vector_model":"text-embedding-ada-002","vector_score":"inner_product"}

Trial variation

[{"lifecycles":2,"recall_at_20_range":[0.335447,0.335447],"variant":"Antfly lexical · default text"},{"lifecycles":2,"recall_at_20_range":[0.359294,0.359738],"variant":"Antfly dense · official vectors"},{"lifecycles":2,"recall_at_20_range":[0.403483,0.404468],"variant":"Antfly built-in RRF · default text"},{"lifecycles":2,"recall_at_20_range":[0.45382,0.45382],"variant":"Antfly lexical · relation-expanded text"},{"lifecycles":2,"recall_at_20_range":[0.488264,0.49273],"variant":"Antfly built-in RRF · relation-expanded text"}]

Retrieval systems

Antfly lexical · default text Native lexical retrieval measured
Antfly dense · official vectors Native ANN over official vectors measured
Antfly built-in RRF · default text Native lexical+dense fusion · built-in RRF measured
Antfly lexical · relation-expanded text Native lexical retrieval measured
Antfly built-in RRF · relation-expanded text Native lexical+dense fusion · built-in RRF measured
Upstream exact VSS Exact official-vector baseline measured
Upstream BM25 Upstream lexical baseline measured
Chroma lexical · default text Native database retrieval unsupported
Chroma dense · official vectors Native database retrieval measured
Chroma hybrid · default text Native database retrieval unsupported
Chroma lexical · relation-expanded text Native database retrieval unsupported
Chroma hybrid · relation-expanded text Native database retrieval unsupported
Elasticsearch lexical · default text Native database retrieval measured
Elasticsearch dense · official vectors Native database retrieval measured
Elasticsearch hybrid · default text Native database retrieval · built-in score sum measured
Elasticsearch lexical · relation-expanded text Native database retrieval measured
Elasticsearch hybrid · relation-expanded text Native database retrieval · built-in score sum measured
Neo4J lexical · default text Native database retrieval measured
Neo4J dense · official vectors Native database retrieval measured
Neo4J hybrid · default text Native database retrieval · in-database query measured
Neo4J lexical · relation-expanded text Native database retrieval measured
Neo4J hybrid · relation-expanded text Native database retrieval · in-database query measured
Pgvector lexical · default text Native database retrieval measured
Pgvector dense · official vectors Native database retrieval measured
Pgvector hybrid · default text Native database retrieval · in-database query measured
Pgvector lexical · relation-expanded text Native database retrieval measured
Pgvector hybrid · relation-expanded text Native database retrieval · in-database query measured
Weaviate lexical · default text Native database retrieval measured
Weaviate dense · official vectors Native database retrieval measured
Weaviate hybrid · default text Native database retrieval · built-in RRF measured
Weaviate lexical · relation-expanded text Native database retrieval measured
Weaviate hybrid · relation-expanded text Native database retrieval · built-in RRF measured
Published · GraphRAFT dataset-trained LLMs, Cypher templates, graph retrieval, reranking full synthetic test; Recall@20 not reported
Published · AF-Retriever zero-shot LLM, graph retrieval, vector search, pairwise reranking full synthetic test; Recall@20 not reported
Published · HybGRAG LLM-assisted hybrid graph and text retrieval full synthetic test; Recall@20 not reported
Published · GritLM-7B original STaRK dense baseline full synthetic test
Published · multi-ada-002 original STaRK multivector baseline full synthetic test

Published comparison sources

GraphRAFT full synthetic test; Recall@20 not reported dataset-trained LLMs, Cypher templates, graph retrieval, reranking Source
AF-Retriever full synthetic test; Recall@20 not reported zero-shot LLM, graph retrieval, vector search, pairwise reranking Source
HybGRAG full synthetic test; Recall@20 not reported LLM-assisted hybrid graph and text retrieval Source
GritLM-7B full synthetic test original STaRK dense baseline Source
multi-ada-002 full synthetic test original STaRK multivector baseline Source

Peer versions

Chroma1.0.0
Elasticsearch9.4.1
Neo4J5.26.29
PgvectorPostgreSQL 16.14 (Debian 16.14-1.pgdg12+1); pgvector 0.8.5
Weaviate1.38.2

Evidence digests

Receipt: a694c48716a2328d5adffbc75ef7f5f96ee8d9e405ae1b9d261a0325784d4bfa
Aggregate: 9d258c5649d8341f20a147ea432d30d4af3eebbfe2b091aa0ef0a6fec20619e7
Provenance: 3136ce666957fd8600a7ee5d692a63cc724d9f4dad06052163e531fb10b37814
Harness commit: f4d6b06ddd7ede36a27827d11d653f939a3a2fdb

Selected measurement

Completed: 5 Sep 2026 · 15:40 UTC
Antfly: v0.2.1-rc.3 · 4 September 2026 · 03:12 UTC
Runtime: 41.7 min
Platform: Linux · arm64
Machine: Apple M4 Max · 10 CPU · 27.3 GB
Build: ReleaseFast

STaRK-Prime Recall@20

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast) · linux-arm64 · Apple M4 Max · Official 2,801-query split · Higher is better

STaRK-Prime retrieval quality

Antfly v0.2.1-rc.3 · bb8a284d

Method	Hit@1 %	Hit@5 %	Recall@20 %	MRR %
Antfly built-in RRF · relation-expanded text	16.12%	39.41%	49.05%	26.79%
Neo4J hybrid · relation-expanded text	17.35%	38.52%	48.40%	27.16%
Weaviate hybrid · relation-expanded text	18.03%	39.13%	48.19%	27.73%
Antfly lexical · relation-expanded text	19.81%	40.41%	45.38%	28.72%
Elasticsearch hybrid · relation-expanded text	18.39%	38.13%	43.91%	27.11%
Weaviate lexical · relation-expanded text	17.99%	37.45%	43.80%	26.69%
Elasticsearch lexical · relation-expanded text	17.78%	36.99%	43.06%	26.34%
Neo4J lexical · relation-expanded text	17.78%	36.99%	43.06%	26.34%
Antfly built-in RRF · default text	13.69%	35.40%	40.40%	23.26%
Weaviate hybrid · default text	14.10%	34.59%	39.24%	23.26%
Neo4J hybrid · default text	13.53%	34.52%	39.21%	22.82%
Published · GritLM-7B	15.57%	33.42%	39.09%	24.11%
Published · multi-ada-002	15.10%	33.56%	38.05%	23.49%
Upstream exact VSS	12.64%	31.49%	36.00%	20.99%
Antfly dense · official vectors	12.05%	30.72%	35.95%	20.43%
Elasticsearch dense · official vectors	12.64%	31.42%	35.78%	20.96%
Pgvector dense · official vectors	12.57%	31.10%	35.55%	20.79%
Weaviate dense · official vectors	12.89%	31.49%	35.34%	21.08%
Chroma dense · official vectors	12.75%	30.95%	34.94%	20.76%
Neo4J dense · official vectors	12.35%	30.74%	34.42%	20.46%
Antfly lexical · default text	14.64%	29.61%	33.54%	21.39%
Elasticsearch hybrid · default text	12.89%	28.24%	32.66%	19.81%
Weaviate lexical · default text	12.78%	27.35%	31.77%	19.48%
Neo4J lexical · default text	12.78%	27.28%	31.64%	19.31%
Elasticsearch lexical · default text	12.78%	27.28%	31.58%	19.31%
Upstream BM25	12.75%	27.92%	31.25%	19.52%
Pgvector hybrid · relation-expanded text	6.50%	21.92%	30.43%	13.51%
Pgvector hybrid · default text	7.64%	21.60%	29.35%	13.86%
Pgvector lexical · relation-expanded text	0.68%	2.28%	3.60%	1.49%
Pgvector lexical · default text	0.57%	2.07%	3.07%	1.28%
Chroma lexical · default text	—	—	—	—
Chroma hybrid · default text	—	—	—	—
Chroma lexical · relation-expanded text	—	—	—	—
Chroma hybrid · relation-expanded text	—	—	—	—
Published · GraphRAFT	63.70%	75.40%	—	69.00%
Published · AF-Retriever	46.20%	63.70%	—	54.00%
Published · HybGRAG	28.60%	41.40%	—	34.50%

Container memory observations

Antfly v0.2.1-rc.3 · bb8a284d

Engine	Lifecycle evidence	Demand memory MB	Observed range MB
Antfly	Two fresh lifecycles · exploratory	9,810.9 MB	9,732.8 MB–9,889.0 MB
Chroma	One retained lifecycle · 2026-08-29	999.9 MB	One lifecycle
Elasticsearch	One retained lifecycle · 2026-08-29	5,090.5 MB	One lifecycle
Neo4J	One retained lifecycle · 2026-08-29	7,090.5 MB	One lifecycle
Pgvector	One retained lifecycle · 2026-08-29	258.0 MB	One lifecycle
Weaviate	One retained lifecycle · 2026-08-29	3,456.9 MB	One lifecycle

retrieval-stark-mag

complete

MAG

Official 2,665-query STaRK-MAG retrieval quality over 700,244 paper candidates, with one fresh rc2 Antfly container-footprint observation.

Methodology scope · protocol · interpretation

STaRK-MAG in Antfly Circus

This lane evaluates paper retrieval over 700,244 official candidates and the complete official 2,665-query test split. Candidate identity uses stable official numeric paper candidate IDs; quality uses the official STaRK evaluator with official text-embedding-ada-002 vectors.

Terms

Lexical: full-text ranking over serialized paper text.
Dense: nearest-neighbor search over the official embeddings.
RRF: reciprocal-rank fusion of lexical and dense rankings.
Relation-expanded: paper text with flattened graph-relation context.
Recall@20: mean fraction of gold paper IDs returned in the first 20 results.

Evidence scope

Quality covers the complete official split. Published reference rows retain their reported metric coverage and execution setting; LLM-assisted systems are not database-native equivalents. Memory and qualified Docker storage are individual observations from one fresh lifecycle; no variance, ratio, or comparative footprint claim is selected. Latency is a local diagnostic.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: retrieval-stark-mag
Domain: retrieval/knowledge-base
Source: https://github.com/snap-stanford/stark
Known Antfly versions: v0.2.1-rc2
Enabled: yes

Benchmark parameters

{"candidate_identity_sha256":"584ec028e9c92616f44e0a462f0c2d088af138a0e40ff7f3c50f6deab8eb060b","dataset":"snap-stanford/stark","dataset_revision":"88269e23e90587f99476c5dd74e235a0877e69be","queries":2665,"records":700244,"vector_dimensions":1536,"vector_model":"text-embedding-ada-002","vector_score":"inner_product"}

Retrieval systems

Antfly lexical · default text Native lexical retrieval 2,665 queries 373.79 ms mean
Antfly dense · official vectors Native dense retrieval 2,665 queries 106.89 ms mean
Antfly built-in RRF · default text One native hybrid request 2,665 queries 576.41 ms mean
Antfly lexical · relation-expanded text Native lexical retrieval 2,665 queries 442.60 ms mean
Antfly built-in RRF · relation-expanded text One native hybrid request 2,665 queries 729.27 ms mean
Upstream exact VSS Exact official-vector baseline 2,665 queries 21.20 ms mean
Upstream BM25 Pinned upstream lexical baseline 2,665 queries 4.40 ms mean

Published comparison sources

AF-Retriever full synthetic test; Recall@20 not reported zero-shot LLM, graph retrieval, vector search, pairwise reranking Source
GraphRAFT full synthetic test; Recall@20 not reported dataset-trained LLMs, Cypher templates, graph retrieval, reranking Source
HybGRAG full synthetic test; Recall@20 not reported LLM-assisted hybrid graph and text retrieval Source
multi-ada-002 full synthetic test original STaRK multivector baseline Source
voyage-large-2-instruct full synthetic test original STaRK dense baseline Source

Peer versions

Peer versions were not recorded in the published result fields.

Evidence digests

Receipt: 6fe666a90ec3a2fbdc6ff4100fcec2fe97b8b35fca27309ab3e01a30ffa29d2f
Aggregate: e0134c6b4b67c8e540bc0d4eb6561af0fbfdc0e27fc4281e5932b65ac7478498
Provenance: a858d3d5fa807f829772d390593a208923a4b59fa5cfe29505ad2a3964ee7353
Harness commit: 598cdd0483de5b51ea562f8ff11dc9ca2ae9d4a3

Selected measurement

Completed: 1 Sep 2026 · 07:54 UTC
Antfly: v0.2.1-rc2 · 30 August 2026 · 21:48 UTC
Runtime: 263.4 min
Platform: Linux · ELF 64-bit LSB executable, ARM aarch64, version 1 (SYSV), statically linked, stripped
Machine: Apple M5 Pro · 8 CPU · 25.2 GB
Build: ReleaseFast · Zig antfly 0.2.1-rc2 (zig runtime)

STaRK-MAG Recall@20

Official full synthetic test · Antfly rc2 and original-paper full-test baselines · Higher is better

STaRK-MAG retrieval quality

Antfly v0.2.1-rc2 · 4be5a0e9

Method	Hit@1 %	Hit@5 %	Recall@20 %	MRR %
Antfly lexical · relation-expanded text	52.76%	72.61%	72.18%	61.69%
Antfly built-in RRF · relation-expanded text	42.89%	68.82%	70.38%	54.44%
Antfly built-in RRF · default text	32.53%	52.83%	52.76%	41.72%
Published · multi-ada-002	25.92%	50.43%	50.80%	36.94%
Published · voyage-large-2-instruct	30.06%	50.58%	50.49%	39.66%
Upstream exact VSS	29.08%	49.61%	48.36%	38.23%
Antfly dense · official vectors	27.73%	48.89%	48.36%	37.26%
Antfly lexical · default text	27.92%	45.55%	46.11%	35.91%
Upstream BM25	25.85%	45.25%	45.69%	34.56%
Published · AF-Retriever	78.60%	91.40%	—	84.00%
Published · GraphRAFT	71.10%	85.30%	—	76.90%
Published · HybGRAG	65.40%	75.30%	—	69.80%

Container footprint observation

Antfly v0.2.1-rc2 · 4be5a0e9

Engine	Lifecycle evidence	Demand memory GiB	Cache-inclusive GiB	Final allocated storage GiB
Antfly	One fresh lifecycle · descriptive observation	17.018 GiB	21.264 GiB	12.080 GiB

iii

retrieval-stark-amazon

partial

Amazon

Complete 1,642-query STaRK-Amazon default-text adapter study over 957,192 product candidates, with relation-expanded construction retained as unavailable scale evidence.

Methodology scope · protocol · interpretation

STaRK-Amazon default-text adapter study

Scope

This exploratory lane evaluates six Antfly query formulations over 957,192 official product candidates and all 1,642 synthesized test queries. Default documents contain upstream product title, description, review, and customer Q&A text. Every lexical row is one Antfly request; hybrid rows add the official ada-002 query vector in the same request and use built-in RRF.

The all-term formulation retains every unique lowercase ASCII-alphanumeric query term and joins them by OR without the legacy stopword, minimum-length, or first-20 filters. IDF top-20 selects terms using document frequency without qrels. Metrics are recomputed from returned top-20 IDs and official qrels.

Evidence quality

Default text has six of six valid rows from one complete lifecycle. Memory and storage are descriptive single observations. Latency is a local diagnostic and is kept in Run details. Published BM25 and ada-002 values are external Table 6 references, not same-run controls.

Relation-expanded coverage is zero of six: No relation-expanded quality row was accepted because no attempted lifecycle ingested all official candidates and reached the final visibility barrier. No partial relation index was scored. Relation expansion means STaRK’s application-side brand, color, category, also-bought, and also-viewed graph context flattened into text; it is not native graph traversal.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: retrieval-stark-amazon
Domain: retrieval/knowledge-base
Source: https://github.com/snap-stanford/stark
Known Antfly versions: v0.2.1-rc2
Enabled: yes

Benchmark parameters

{"candidate_id_sha256":"c15dbc912e6494145295c9178e2848374b23b2291bf201c961b03f7b36edef8b","candidates":957192,"corpus_sha256":"aa52c91035b4aef826bf1e9ab70c3c9d264b0d949e08e349423bcab56996b832","dataset_revision":"88269e23e90587f99476c5dd74e235a0877e69be","name":"amazon","queries":1642}

Peer versions

Peer versions were not recorded in the published result fields.

Evidence digests

Receipt: 00d56bdfef2a36b31d0c256d4201210c63da0ed9a46a7fd6bae42d881d37656f
Aggregate: a2c587a79c8b1e60dd18677a33d3c4512d3970d69cdcabb2a1ea8184e45b4436
Provenance: 9536848b7e88b248ef41fee2bc710fdc41423eafff0b6eb76a8274cc128806f8
Harness commit: 3d85a0a6ab985ad3f6a6abf9281c927cc8277ee6aa986cabc55ed3dcc1f514e0

Selected partial evidence

Completed: 3 Sep 2026 · 07:32 UTC
Antfly: v0.2.1-rc2 · 30 August 2026 · 21:48 UTC
Runtime: 4.1 h
Platform: darwin · arm64
Machine: Apple M5 Pro · 8 CPU · 35.2 GiB Docker VM
Build: ReleaseFast · Zig antfly 0.2.1-rc2 (zig runtime)

STaRK-Amazon default-text Recall@20

Antfly v0.2.1-rc2 · Docker Desktop Linux/arm64 on Apple M5 Pro · 957,192 products · 1,642 test queries · Higher is better

Default-text query formulation

Antfly v0.2.1-rc2 · 4be5a0e9

Method	Hit@1 %	Hit@5 %	Recall@20 %	MRR@20 %	Official queries
Built-in RRF · all-term OR	49.70%	74.06%	60.75%	60.10%	1,642 / 1,642
Built-in RRF · first-20 OR	48.54%	72.90%	59.95%	59.26%	1,642 / 1,642
Lexical · all-term OR, uncapped	47.93%	68.70%	55.85%	57.28%	1,642 / 1,642
Lexical · IDF top-20 OR	48.23%	68.94%	55.48%	57.38%	1,642 / 1,642
Lexical · filtered OR, uncapped	46.53%	68.27%	54.96%	56.00%	1,642 / 1,642
Lexical · first-20 filtered OR	46.35%	67.66%	54.44%	55.81%	1,642 / 1,642
Published · BM25	44.94%	67.42%	53.77%	55.30%	Published full test
Published · ada-002	39.16%	62.73%	53.29%	50.35%	Published full test

Representation coverage and default footprint

Antfly v0.2.1-rc2 · 4be5a0e9

Representation	Valid rows	Evidence	Demand memory GiB	Cache-inclusive peak GiB	Final allocated storage GiB
Default text	6 / 6 valid	One complete lifecycle · descriptive	22.985 GiB	32.069 GiB	8.689 GiB
Relation-expanded	0 / 6 valid	Unavailable · construction did not reach full visibility	—	—	—

agent-effort-quickstart

complete

Agent implementation effort

Implementation effort for agents completing equivalent Antfly and peer integration tasks.

Methodology scope · protocol · interpretation

Agent Access Effort

Question

Given a raw corpus and a named access system, how much agent work is required to make the corpus usable and complete grounded retrieval tasks?

This is an end-to-end product-choice benchmark. Grep is a first-class subject, not merely an engine-quality baseline: it has almost no activation cost and is how coding agents commonly search local data. Antfly, Chroma, and Milvus must earn their indexing and setup cost through easier or more effective retrieval.

Clean pilot protocol

The checked result is the one-trial-per-system clean-20260821 internal pilot. A fresh pi session using openrouter/deepseek/deepseek-v4-flash ran each subject sequentially:

grep (ripgrep from the Debian bookworm image),
Antfly v0.2.0, commit 56a1b1a591f5db0b80017e425ad0c449f52f38fe,
Chroma 1.5.9,
Pymilvus 3.0.0 with Milvus Lite 3.0.

Each task image contained 240 synthetic JSONL documents. Eight documents held fictional facts; 232 deterministic distractors shared vocabulary but not the answer-bearing entities. Every document also carried a precomputed 256-dimensional deterministic token-hash vector. This avoids model-download and embedding-runtime differences in the activation measurement. The questions, answers, and evidence document IDs are fixed by the harness.

Software was preinstalled but not configured. Environment image builds and software installation were excluded. The agent received one concise subject usage guide, the raw corpus, and helper commands for producing compatible query vectors and recording milestones.

Trial sequence

Configure the assigned system and load/index all 240 documents.
Verify its retrieval surface is usable. Queries while an index is still building do not qualify.
Record the ready milestone.
Reveal the eight questions only after readiness.
Retrieve each answer through the assigned system and record the answer plus its evidence document ID.

After a database subject records readiness, the harness removes the raw corpus. This prevents the question-answering phase from silently falling back to grep. The grep row retains the corpus because the file is its retrieval surface.

The verifier requires:

all eight exact answers,
all eight expected evidence document IDs,
a ready marker before every grounded milestone,
the expected live or persistent system artifact,
no post-readiness raw-corpus access for database rows.

The clean pilot did not independently execute a subject-specific readiness probe at the instant of the marker. Trajectory review found that Milvus marked ready while its collection was released; its first post-ready query failed and the agent loaded the collection afterward. The Milvus ready time is therefore invalid and is not published.

Metrics

Ready seconds: agent-start to the ready marker, retained only when the trajectory shows the assigned retrieval surface was usable at that point.
All grounded seconds: agent-start to completion of all eight grounded answers. Agents recorded the answers as a batch in this pilot, so this is a panel-completion metric, not steady-state per-query latency.
Work tool calls: pi tool calls excluding direct effort-mark and effort-questions bookkeeping calls.
Failure-bearing calls: calls whose tool result was an error or whose retained output contained a concrete traceback, HTTP/API failure, invalid vector dimensions, or failed command. This catches curl pipelines that returned exit zero despite an API failure.
Gross tokens: ordinary input, cache-read input, and output tokens summed.
Agent cost: Harbor/pi provider accounting.
Success rate: grounded answers divided by eight; correctness is a bar.

Checked result

System	Valid ready	All 8 grounded	Work tool calls	Failure-bearing calls	Gross tokens	Agent cost
grep	16.3 s	42.6 s	18	0	152,279	$0.0046
Chroma	35.2 s	65.3 s	18	0	168,956	$0.0066
Milvus Lite	invalid	127.9 s	33	7	328,205	$0.0064
Antfly	211.9 s	272.7 s	53	6	1,581,093	$0.0248

All four rows grounded 8/8 answers. Milvus violated the readiness protocol. On this small exact-entity workload, grep completed the grounded panel fastest; no indexed subject recovered its activation cost.

Trajectory audit

Raw tool-call totals were 28 grep, 28 Chroma, 35 Milvus, and 63 Antfly, but they are not directly comparable. Grep, Chroma, and Antfly each spent ten separate calls on benchmark markers; the Milvus agent invoked its eight grounded markers from inside one generated Python script. The checked table therefore reports direct work calls after removing only explicit marker calls.

Antfly used 43 calls before its ready marker. Its first table, external-vector index, and batch load were substantially complete by call 13. A malformed manual vector probe then returned InvalidVectorDimensions; the agent misdiagnosed that query error as broken ingestion, restarted Antfly, reloaded without the vector index, investigated zero coverage, and finally dropped/recreated/reloaded the table in the correct order. That diagnostic spiral accounts for most of the 211.9-second activation time.

Antfly also emitted a 42,783-character unprojected index-status response early in the session. Replaying that result through the remaining turns contributed to 1.45 million cache-read tokens. Gross traffic is intentionally retained, but uncached input was 122,875 tokens; the gross-token ratio should not be read as an equivalent billing ratio.

The one-page subject guides were not equally executable. Chroma received a working client/collection snippet and had no failure-bearing call. Milvus received prose describing the desired schema, then spent ten introspection calls reconciling post-training Pymilvus 3.0 schema and index APIs. The Antfly guide incorrectly instructed the agent to create a redundant full-text index even though v0.2.0 created full_text_index_v0 with the table; that caused one of its six failure-bearing calls.

Finally, the exact-entity questions were answered through Antfly full-text search, while the task still required Antfly’s vector index to be ready. The vector setup was therefore pure activation tax in this workload. A successor should either let each system choose the minimum sufficient retrieval path or separate exact and semantic panels.

Scope and interpretation

This is intentionally an internal pilot, not a honed publication result:

one trial per system,
one agent/model,
small synthetic corpus,
exact entity anchors favor grep,
deterministic hash vectors rather than a production embedding model,
software acquisition and live website UX excluded,
no memory, storage, or backend request-latency claim.

The result validates the benchmark shape and exposes onboarding friction. It does not estimate model variance or the query-count break-even point. A later campaign can reuse the same phase boundaries on larger semantic and long-document corpora without expanding this pilot’s claims.

Reproduction and retained evidence

Harness: benchmarks/agent-access-effort-harness/access_effort.py
Checked aggregate: benchmarks/agent-access-effort-harness/result.json
Deterministic contract: make agent-access-effort-smoke
Paid run: make agent-access-effort-run AAE_RUN_ID=<id>
Reprojection: make agent-access-effort-report AAE_RUN_ID=<id>

Raw Harbor trajectories remain local under results/agent-access-effort/<run-id>/jobs/; they are excluded from the site snapshot because they contain large model transcripts and task data.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: agent-effort-quickstart
Domain: agent-effort
Source: https://github.com/antflydb/antfly-circus
Known Antfly versions: v0.2.*
Enabled: yes

Benchmark parameters

{"result_rows":4}

Peer versions

Peer versions were not recorded in the published result fields.

Evidence digests

Receipt: e2ff2133c13b55f60b080aa7a37ef41d575a44144482c85415c98ace9ecf01b2
Aggregate: f6082996bae217f899bd77f8316af8544d5fe3578157d65ba4810f4245e9435d
Provenance: fdd85399dfdc6529020b385940c29077d99c68bffaa217eb29e9b1e3501bd772
Harness commit: 96db7cdd5f0e6743c4c6b86d4af7c85e43502a8d

Scope notes

Internal one-trial pilot on a 240-document synthetic exact-entity workload; software installation, live website UX, and model variance are out of scope.
Milvus grounded 8/8 but violated the readiness protocol; its ready time is not published. Work tool calls exclude direct benchmark marker calls.
Latest fallback: newest reviewed tagged evidence from v0.2.0.

Selected measurement

Completed: 21 Aug 2026 · 23:27 UTC
Antfly: v0.2.0 · 10 August 2026 · 22:51 UTC
Runtime: 0s
Platform: darwin · arm64
Machine: Apple M5 Pro · 15 CPU · 51.5 GB
Build: optimization mode not captured · Zig compiler version not captured

Internal one-trial pilot on a 240-document synthetic exact-entity workload; software installation, live website UX, and model variance are out of scope.

Milvus grounded 8/8 but violated the readiness protocol; its ready time is not published. Work tool calls exclude direct benchmark marker calls.

Latest fallback: newest reviewed tagged evidence from v0.2.0.

Result summary

Antfly v0.2.0 · 56a1b1a5

System	Grounded	Ready s	All grounded s	Work tool calls	Failure-bearing calls	Gross tokens	Agent cost USD	Status
grep	1	16.3 s	42.6 s	18	0	152,279	0.005 USD	passed
antfly	1	211.9 s	272.7 s	53	6	1,581,093	0.025 USD	passed
chroma	1	35.2 s	65.3 s	18	0	168,956	0.007 USD	passed
milvus	1	—	127.9 s	33	7	328,205	0.006 USD	readiness protocol violation

graph-benchmark

complete

Graph

Graph query performance, Pokec-small cross-engine diagnostics, official LSQB capability, and bounded SNB Interactive qualification.

Methodology scope · protocol · interpretation

Graph Database Benchmark v2 Methodology

Scope and provenance

This benchmark has two lanes and does not calculate a composite winner. LSQB-derived is an Antfly-owned anchored microbenchmark over LSQB data. The Pokec suite is a clean-room implementation informed by the public categories and workload ratios described by Memgraph’s Benchgraph material. It reuses the public Pokec import files, not Benchgraph implementation code. Neither lane is an audited LDBC result.

The scorecard keeps these measurements separate:

Lane	Scorecard metrics	Direction
LSQB-derived F2	warm serial p50, warm serial p99	latency lower
Pokec W1	completed QPS, peak process RSS	QPS higher; RSS lower

Full statistics, errors, run ranges, and raw samples remain mandatory even when the scorecard is used.

Engines and equal client work

The comparison is Antfly, Neo4j 5.26.29, and Memgraph 3.12.0. Kuzu is excluded because it is not exercised through a comparable network service. Every timed throughput cell uses the same Go executable, deterministic schedule, quantile implementation, response-consumption rule, worker count, and wall-clock. Antfly is accessed over persistent HTTP/1.1; both peers use the same official Neo4j Go Bolt driver. Transport is part of observed client latency and is reported, not hidden.

Only equivalent User(id) and benchmark-namespace ID indexes are created. There is no engine-specific query tuning. Each run starts from a fresh database and performs complete correctness checks before timing. Mutating cells use a reserved BenchUser namespace so source reads cannot change; that namespace is restored to its 1,024-node ring baseline after every mutating cell. Timed requests are never retried. Errors are retained and exclude a run from the publication gate.

LSQB-derived lane

The pinned source, data loading, parameter selection, BLAKE3 result oracle, and N1/P2/F2 definitions are specified in graph-lsqb-derived.md. The public LSQB-derived metric is warmed serial latency for this exact endpoint-filtered lookup, returning matching Post IDs:

(Forum)-[:CONTAINER_OF]->(Post)-[:HAS_TAG]->(Tag {id: $tag_id})

Unfiltered P2 C12 throughput remains a retained diagnostic. It is not part of the graph scorecard or public filtered-lookup claim. Default, medium, and full use LSQB SF0.003, SF0.1, and SF1 respectively.

Pokec data and parameter oracle

Profiles use the public Memgraph Pokec import files:

Profile	Dataset	Users	Directed `FRIEND` edges	Anchors
quick	Pokec-small	10,000	121,716	12
medium	Pokec-medium	100,000	1,768,515	48
full	Pokec-large	1,632,803	30,622,564	128

The harness records the downloaded source SHA-256 and refuses unexpected node or edge counts. Anchors are selected deterministically across out-degree deciles with seed 0xB37C4. Every selected anchor must return its complete result below 900 rows through four hops; this stays below rc18’s 1,000 pattern match ceiling rather than comparing truncated results.

Expansion semantics are one endpoint result per directed walk. Antfly uses a chain of fixed one-hop pattern steps. Cypher uses one fixed MATCH clause per hop, avoiding vendor differences in variable-length path uniqueness. The offline SQLite oracle stores the exact result count and canonical BLAKE3 digest including multiplicity for every parameter. Aggregates and shortest path have exact scalar oracles. All 101 quick-profile checks per engine/run must pass before timing. Writes are executed and verified in the isolated benchmark namespace.

Pokec operations

ID	Operation
R1	exact indexed node lookup
WN	insert a new benchmark node
U1	increment one benchmark-node property
WE	insert one directed benchmark edge
AG1	age buckets and counts
AG2	age count/min/max/sum/average
E1–E4	exact fixed 1-, 2-, 3-, or 4-hop directed expansion
E2F	exact 2-hop expansion with endpoint `age >= 18`
N2	concatenated exact 1-hop and exact 2-hop neighborhood
SP	directed unweighted shortest path, maximum depth 8

Every operation has an unwarmed serial observation and a prewarmed serial distribution. Isolated throughput uses 12 clients. Each non-mutating operation also receives a 70% operation / 30% write cell, split evenly between node and edge insert. The deterministic realistic workloads are:

W1: 20% analytical, 40% point read, 10% update, 30% write;
W2: 70% point read, 30% write;
W3: 50% point read, 50% write;
W4: 30% point read, 70% write.

The quick profile uses one-second isolated/mixed cells and two-second W1–W4 cells. Medium uses 5/10 seconds; full uses 15/30 seconds. Warmup is untimed. Every successful timed request is retained in JSONL. Reports contain completed QPS, error counts, p50/p95/p99, per-operation statistics, and peak PID RSS.

Persistent database volume

The honed LSQB SF0.1 F2 lane creates a new, run-labeled Docker local volume for every engine and repetition. Only the complete writable database root is measured (/data for Antfly and Neo4j, /var/lib/memgraph for Memgraph); read-only dataset/tool volumes and client scratch are excluded. A digest-pinned Alpine probe captures whole-volume allocated and apparent bytes once at empty, service-ready-before-ingestion, and post-workload, then at the verified post-stop final barrier. Final allocated bytes are the headline.

All three storage values, their arithmetic mean and range, apparent-byte diagnostics, barrier samples, volume manifests, and lifecycle receipts are retained. A provisional stop timeout remains visible but cannot support a comparative ratio.

Runs, ordering, and reporting

Each profile requires three clean process runs. Engine order rotates by run and uses a different rotation between lanes. Public serial point estimates are the medians of the three run-level p50, p95, and p99 values. Every result row also retains the three run-level percentile records, their min–max ranges, pooled sample percentiles as diagnostics, and all raw samples. Load/index readiness is diagnostic and is never included in query metrics.

summary.json is the machine-readable source of truth. The Markdown report contains the full cell table; scorecard.svg is only the compact two-panel view. There is deliberately no geometric mean or composite rank.

The honed LSQB SF0.1 F2 lane caches only the complete three-engine cohort. Promotion requires Antfly, Neo4j, and Memgraph to each retain three fresh database constructions and process runs, 15,000 timed samples, all three run-level percentile records and ranges, three complete storage receipts and their allocated-byte mean/range, 1,000/1,000 correctness, a valid canonical receipt, and the quiet-host record. The cache identity binds the Antfly subject, both peer image digests, the Linux client and storage-probe image, dataset manifest, harness sources, and protocol. A hit materializes the entire cohort; per-engine cache mixing is not permitted.

Internal fresh-service F2 readiness and convergence

The honed and Circus profiles retain a fresh-service diagnostic that measures how quickly a preloaded graph service becomes useful and settles into its warm filtered-two-hop behavior. It is graph-specific: readiness is followed immediately by the same exact LSQB SF0.1 F2 request used by the warm latency lane. It is not a general process-startup or system-wide Antfly claim.

This cohort is deliberately internal. It is attached to the canonical graph run report and structured result, but the public benchmark-page renderer does not render its table. It is never eligible for the honed publication cache: each honed or gauntlet graph invocation collects it afresh with make graph-f2-warmup-run. The retained diagnostic contract requires:

the same Antfly binary, pinned Neo4j and Memgraph images, official LSQB SF0.1 dataset, and Linux/arm64 Docker environment as the primary graph lane;
a recorded physical-host state, including whether the honed quiet-host assertion was active, without treating a diagnostic run as publication data;
one database construction followed by five fresh service lifecycles per engine, with balanced engine ordering;
restart-to-ready measured from immediately before service launch through the first successful engine-native probe: Antfly GET /readyz, Neo4j cypher-shell RETURN 1 plus the pinned-version check, and Memgraph autocommit SHOW VERSION over Bolt;
the first F2 latency and first-100 p50/p95 from a fixed 100-anchor panel selected by SHA-256 rank independently of result cardinality;
convergence at the first point where three consecutive adjacent 100-query window p50 changes are each within 5%, with a 10,000-query ceiling;
steady-state p50/p95 from five deterministic sweeps over all 1,000 anchors after convergence;
every timed result checked against the independent count+BLAKE3 oracle, with all 1,000 anchors covered in every engine/lifecycle; and
median-of-five run metrics with complete run ranges, raw timestamped samples, lifecycle logs, host evidence, exact schedules, and a canonical receipt.

These seven values are an indivisible internal reporting family: restart-to-ready, first-query, first-100 p50, first-100 p95, queries-to-stable-p50, steady p50, and steady p95. The retained report must show all seven for all three engines; it must not headline convergence while omitting the steady-state latency guardrail or Memgraph.

Qualification and publication

The default command is a small, complete optimization loop with a target wall time below 15 minutes. Medium and full are explicit diagnostic commands. A mixed native-macOS/container run is qualification-only because its process RSS views are not comparable across engines.

The release-facing honed F2 lane is a separate, environment-qualified publication protocol. Antfly, Neo4j, and Memgraph all run sequentially inside the same Docker Desktop Linux/arm64 VM on an explicitly quiescent Apple Silicon host. The published claim must name that environment and is limited to warm serial filtered two-hop latency; it is not a bare-metal Linux result or a claim about general graph-database performance. Publication requires:

the exact v0.2.0 Linux/arm64 binary and expected SHA-256;
the pinned Neo4j 5.26.29, Memgraph 3.12.0, and Linux client image digests;
official LSQB SF0.1 with 432,235 nodes and 1,827,523 relationships;
three fresh database constructions and process runs per engine, each on a newly created labeled database volume;
five warmed serial sweeps per run over 1,000 deterministic anchors;
1,000/1,000 count+BLAKE3 correctness in every engine/run and zero timed errors;
median run-level p50/p95/p99 with all run ranges, pooled diagnostics, raw samples, lifecycle logs, and the physical-host record retained; and
a canonical receipt for the indivisible three-engine cohort.

The broader graph-v2/Pokec publication gate remains native-Linux-only and is not satisfied by this bounded F2 artifact.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: graph-benchmark
Domain: graph benchmark
Source: https://github.com/ldbc/lsqb
Known Antfly versions: v0.1.3, v0.2.*
Expected duration: 100 min
Enabled: yes

Benchmark parameters

{"execution_environment":{"container_runtime":"Podman podman version 6.1.1","controller_platform":"darwin-arm64","processor":"Apple M4 Max","service_platform":"linux-arm64","vm_cpus":10,"vm_memory_bytes":29347610624,"vm_memory_gib":27.3},"historical_peer_trial_variation":[{"engine":"memgraph","ranges":{"demand_working_set":{"maximum":438.550528,"mean":435.0102186666667,"minimum":433.000448,"unit":"MB"},"final_database_volume":{"maximum":311.88992,"mean":311.887189,"minimum":311.885824,"unit":"MB"},"query_p95":{"maximum":0.15475835000000002,"mean":0.15450830000000002,"minimum":0.1530902,"unit":"ms"}}},{"engine":"neo4j","ranges":{"demand_working_set":{"maximum":4937.388032,"mean":4928.65536,"minimum":4922.712064,"unit":"MB"},"final_database_volume":{"maximum":635.6992,"mean":635.674624,"minimum":635.654144,"unit":"MB"},"query_p95":{"maximum":0.8094312500000002,"mean":0.7950937500000004,"minimum":0.7930104000000001,"unit":"ms"}}}],"peers_not_run":["memgraph","neo4j"],"query":"F2","runs":3,"samples":15000}

Peer versions

Memgraph3.12.0
Neo4j5.26.29

Evidence digests

Receipt: 8757aa2d6333d09eb55a800d0f738347e70c8251fb5f805aa5366c09ab26dc92
Aggregate: 36ba4361fd2de7dcb3bb32dd5b5b8c25cd5f7fd68a467cba60b0c387c6cee109
Provenance: 36ba4361fd2de7dcb3bb32dd5b5b8c25cd5f7fd68a467cba60b0c387c6cee109
Harness commit: 82c699bb7a687b65efc691ec329368494ce8499e

Selected measurement

Completed: 6 Oct 2026 · 07:20 UTC
Antfly: main-09b78df97 · 6 October 2026 · 00:55 UTC
Runtime: 48m 54s
Platform: linux · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Warm serial p95

Antfly main-09b78df97 (09b78df9, ReleaseFast) · linux-arm64 · LSQB-derived SF0.1 F2 · 15,000 samples / three runs · Lower is better · Apple M4 Max · Podman podman version 6.1.1 · 10 VM CPUs / 27.3 GiB · Historical peers, not a matched run

Demand working set

Final database volume

Latency, resources, and served samples

Antfly main-09b78df97 · 09b78df9

Engine	Version	Query	p50 ms	p95 ms	p99 ms	Demand working set MB	Final database volume MB	Served samples
antfly	antfly main-09b78df97 (zig runtime)	F2	1.732	14.999	58.608	2,337.9 MB	405.1 MB	15,000
memgraph	3.12.0	F2	0.115	0.155	0.226	435.0 MB	311.9 MB	15,000
neo4j	5.26.29	F2	0.407	0.795	1.291	4,928.7 MB	635.7 MB	15,000

graph-diagnostics

partial

Pokec-small

Same-host Pokec-small coverage across Antfly, Neo4j, and Memgraph over 29 operation and workload cells.

Methodology scope · protocol · interpretation

Graph Database Benchmark v2 Methodology

Scope and provenance

The scorecard keeps these measurements separate:

Lane	Scorecard metrics	Direction
LSQB-derived F2	warm serial p50, warm serial p99	latency lower
Pokec W1	completed QPS, peak process RSS	QPS higher; RSS lower

Full statistics, errors, run ranges, and raw samples remain mandatory even when the scorecard is used.

Engines and equal client work

LSQB-derived lane

(Forum)-[:CONTAINER_OF]->(Post)-[:HAS_TAG]->(Tag {id: $tag_id})

Pokec data and parameter oracle

Profiles use the public Memgraph Pokec import files:

Profile	Dataset	Users	Directed `FRIEND` edges	Anchors
quick	Pokec-small	10,000	121,716	12
medium	Pokec-medium	100,000	1,768,515	48
full	Pokec-large	1,632,803	30,622,564	128

Pokec operations

Cell identifier	Full operation name
`R1`	exact indexed user lookup returning the stored user document
`WN`	insert a new benchmark user node
`U1`	increment one benchmark-user property
`WE`	add one directed benchmark friendship edge
`AG1`	whole-table age buckets and counts
`AG2`	whole-table age count/min/max/sum/average
`E1–E4`	exact fixed 1-, 2-, 3-, or 4-hop directed expansion
`E2F`	exact 2-hop expansion with endpoint `age >= 18`
`N2`	concatenated exact 1-hop and exact 2-hop neighborhood
`SP`	directed unweighted shortest path, maximum depth 8

Four-hop expansion (E4) returns endpoints reached by exactly four directed hops; one-plus-two-hop neighborhood (N2) concatenates the exact one-hop and exact two-hop neighborhoods (including walk multiplicity). They measure different work and remain separate rows.

Mixed analytical/read/update/write workload (W1): 20% analytical (AG1/AG2), 40% exact indexed user lookup, 10% property update, and 30% write split evenly between node and edge mutation;
Read-heavy mixed workload (W2): 70% exact indexed user lookup and 30% write;
Balanced read/write workload (W3): 50% exact indexed user lookup and 50% write;
Write-heavy mixed workload (W4): 30% exact indexed user lookup and 70% write.

How to interpret representative cells

Within one cell, higher completed QPS and lower p50/p95/p99 indicate better serving performance. QPS values across different cells do not compare equal amounts of work.

Exact indexed user lookup (R1) fetches one known user and returns the stored document. Its isolated cell measures focused point-read behavior with 12 clients and thousands of served samples per run.

Directed unweighted shortest path (SP) invokes each engine’s shortest-path primitive with a maximum depth of eight. The deterministic quick-profile parameters select targets one or two hops away, so this cell demonstrates short bounded pathfinding rather than long-path or high-diameter behavior.

Mixed analytical/read/update/write workload (W1) supplies the broadest database-behavior signal. Twelve clients concurrently issue 20% whole-table age analytics, 40% exact user lookups, 10% property increments, and 30% node or edge writes. Slow analytics or mutation maintenance can therefore delay otherwise-fast reads; the cell intentionally captures this cross-operation interference. Low completion counts make its tail percentiles directional, so reports retain counts and every raw response alongside QPS and latency.

Current Antfly rejects transforms against reserved _edges paths. Its WE compatibility request replaces the complete deterministic benchmark edge set through a whole-document upsert, while Neo4j and Memgraph create one edge. Diagnostic presentations disclose that difference and make no publication or apples-to-apples write-throughput claim.

Persistent database volume

Runs, ordering, and reporting

Internal fresh-service F2 readiness and convergence

the same Antfly binary, pinned Neo4j and Memgraph images, official LSQB SF0.1 dataset, and Linux/arm64 Docker environment as the primary graph lane;
a recorded physical-host state, including whether the honed quiet-host assertion was active, without treating a diagnostic run as publication data;
one database construction followed by five fresh service lifecycles per engine, with balanced engine ordering;
restart-to-ready measured from immediately before service launch through the first successful engine-native probe: Antfly GET /readyz, Neo4j cypher-shell RETURN 1 plus the pinned-version check, and Memgraph autocommit SHOW VERSION over Bolt;
the first F2 latency and first-100 p50/p95 from a fixed 100-anchor panel selected by SHA-256 rank independently of result cardinality;
convergence at the first point where three consecutive adjacent 100-query window p50 changes are each within 5%, with a 10,000-query ceiling;
steady-state p50/p95 from five deterministic sweeps over all 1,000 anchors after convergence;
every timed result checked against the independent count+BLAKE3 oracle, with all 1,000 anchors covered in every engine/lifecycle; and
median-of-five run metrics with complete run ranges, raw timestamped samples, lifecycle logs, host evidence, exact schedules, and a canonical receipt.

Bounded internal Maxi diagnostic source

graph-diagnostics canonicalizes medium Pokec and LSQB-derived SF0.1 instrumentation without changing the honed F2 publication protocol. One balanced three-engine collection produces two independent sub-lanes:

lsqb-derived-anchored-n1-p2-f2-v1 retains separate warm-serial N1, P2, and F2 median-of-three run percentiles, ranges, result-count buckets, served sample counts, and every count+BLAKE3 parameter oracle; and
pokec-graph-operations-v1 retains R1, E1–E4, E2F, N2, SP, AG1, AG2, WN, U1, WE, W1–W4, exact mutation-state checks, and raw schedules on the Pokec-medium corpus.

The default runner passes zero throughput seconds, so it never starts the P2 concurrency workload. It also never starts the five-lifecycle fresh-service cohort. graph-p2-c12-sf01-run and graph-f2-warmup-run retain those protocols as explicit opt-in diagnostics. SF1 and SF10 likewise require explicit scale targets and never enter the default gauntlet.

The finalizer rejects timed errors, missing runs, failed count/hash/state oracles, and any result-budget contact. The canonical result uses graph-diagnostics-v2 with classification internal_diagnostic. PID RSS remains under diagnostic_process_rss; the source declares comparable_resource_metrics: false, emits no memory or storage chart, and defines no composite winner. This source enters the gauntlet and Maxi incubation views only, never the honed allowlist or public graph section.

Qualification and publication

the exact v0.2.0 Linux/arm64 binary and expected SHA-256;
the pinned Neo4j 5.26.29, Memgraph 3.12.0, and Linux client image digests;
official LSQB SF0.1 with 432,235 nodes and 1,827,523 relationships;
three fresh database constructions and process runs per engine, each on a newly created labeled database volume;
five warmed serial sweeps per run over 1,000 deterministic anchors;
1,000/1,000 count+BLAKE3 correctness in every engine/run and zero timed errors;
median run-level p50/p95/p99 with all run ranges, pooled diagnostics, raw samples, lifecycle logs, and the physical-host record retained; and
a canonical receipt for the indivisible three-engine cohort.

The broader graph-v2/Pokec publication gate remains native-Linux-only and is not satisfied by this bounded F2 artifact.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: graph-diagnostics
Domain: graph database diagnostics
Source: https://github.com/ldbc/lsqb
Known Antfly versions: v0.1.3, v0.2.*
Enabled: yes

Benchmark parameters

{"correctness":{"antfly-1":{"failed":0,"oracle":"complete result multiset/count or exact aggregate/path value","passed":101,"rate":1},"antfly-2":{"failed":0,"oracle":"complete result multiset/count or exact aggregate/path value","passed":101,"rate":1},"antfly-3":{"failed":0,"oracle":"complete result multiset/count or exact aggregate/path value","passed":101,"rate":1},"memgraph-1":{"failed":0,"oracle":"complete result multiset/count or exact aggregate/path value","passed":101,"rate":1},"memgraph-2":{"failed":0,"oracle":"complete result multiset/count or exact aggregate/path value","passed":101,"rate":1},"memgraph-3":{"failed":0,"oracle":"complete result multiset/count or exact aggregate/path value","passed":101,"rate":1},"neo4j-1":{"failed":0,"oracle":"complete result multiset/count or exact aggregate/path value","passed":101,"rate":1},"neo4j-2":{"failed":0,"oracle":"complete result multiset/count or exact aggregate/path value","passed":101,"rate":1},"neo4j-3":{"failed":0,"oracle":"complete result multiset/count or exact aggregate/path value","passed":101,"rate":1}},"dataset":{"dataset":"pokec-small","edges":121716,"nodes":10000,"source_sha256":"3e64bffd118c18a23342233f30fc710b753f4ea173a2d166351a28b44976c308","source_url":"https://s3.eu-west-1.amazonaws.com/deps.memgraph.io/dataset/pokec/benchmark/pokec_small_import.cypher"},"total_cells":29,"valid_cells":26}

Peer versions

Memgraph3.12.0
Neo4j5.26.29

Evidence digests

Receipt: 5706f0a25f0eed6d191218ceebaeb2e4c8d74f6e55e055ad3d621c3bf5e138ae
Aggregate: 054c24de6dff36de12b5e605a351d1882943f1fc2c50870fae3284e336305d35
Provenance: 723ed4b22e9ca9fc7505d363c5d9c7a099963bf55c8ee5a118525215d6b8c4a2
Harness commit: f4d6b06ddd7ede36a27827d11d653f939a3a2fdb

Selected partial evidence

Completed: 5 Sep 2026 · 08:14 UTC
Antfly: v0.2.1-rc.3 · 4 September 2026 · 03:12 UTC
Runtime: 8m 16s
Platform: darwin · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Pokec-small throughput by task and engine

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · Apple M4 Max physical host · Antfly native Darwin/arm64 · Neo4j Linux/arm64 Docker · Memgraph Linux/arm64 Docker · Pokec-small · three runs · errorful cells excluded · Each task resets red→yellow→green from lowest to highest QPS; compare within the same task/row only

Pokec-small graph operations

Antfly v0.2.1-rc.3 · bb8a284d

Task	Antfly	Neo4j	Memgraph
Serial read sweep (unwarmed)	QPS 39.8 · p50 0.717 / p95 148.937 / p99 155.431 ms	QPS 58.4 · p50 19.6 / p95 33.8 / p99 37.1 ms	QPS 988.6 · p50 0.3 / p95 4.1 / p99 5.2 ms
Serial read sweep (prewarmed)	QPS 37.1 · p50 0.352 / p95 136.195 / p99 139.711 ms	QPS 580.6 · p50 1.5 / p95 3.6 / p99 4.2 ms	QPS 807.1 · p50 0.3 / p95 5.2 / p99 5.4 ms
Isolated · exact lookup (R1)	QPS 31,530.3 · p50 0.261 / p95 0.956 / p99 1.528 ms	QPS 12,669.9 · p50 0.9 / p95 1.6 / p99 2.4 ms	QPS 25,920.4 · p50 0.4 / p95 0.8 / p99 1.1 ms
Isolated · age buckets (AG1)	QPS 18.6 · p50 634.829 / p95 659.726 / p99 669.917 ms	QPS 5,042.6 · p50 2.1 / p95 3.8 / p99 5.4 ms	QPS 5,775.7 · p50 1.9 / p95 3.3 / p99 4.0 ms
Isolated · age stats (AG2)	QPS 19.1 · p50 616.413 / p95 650.392 / p99 687.198 ms	QPS 4,772.2 · p50 2.1 / p95 4.2 / p99 5.4 ms	QPS 2,935.5 · p50 3.8 / p95 5.5 / p99 6.5 ms
Isolated · 1-hop expansion (E1)	QPS 36,929.5 · p50 0.225 / p95 0.751 / p99 1.196 ms	QPS 7,865.9 · p50 1.2 / p95 2.6 / p99 4.1 ms	QPS 25,184.7 · p50 0.4 / p95 0.8 / p99 1.1 ms
Isolated · 2-hop expansion (E2)	QPS 25,189.7 · p50 0.333 / p95 1.164 / p99 1.791 ms	QPS 7,962.1 · p50 1.3 / p95 2.6 / p99 3.3 ms	QPS 21,020.8 · p50 0.5 / p95 1.1 / p99 1.4 ms
Isolated · 2-hop age filter (E2F)	QPS 9,033.1 · p50 1.011 / p95 3.331 / p99 5.136 ms	QPS 8,342.8 · p50 1.2 / p95 2.5 / p99 3.2 ms	QPS 23,145.7 · p50 0.5 / p95 0.9 / p99 1.3 ms
Isolated · 3-hop expansion (E3)	QPS 9,496.9 · p50 0.877 / p95 3.443 / p99 5.272 ms	QPS 6,183.9 · p50 1.8 / p95 3.0 / p99 3.7 ms	QPS 12,517.3 · p50 0.9 / p95 1.5 / p99 1.9 ms
Isolated · 4-hop expansion (E4)	QPS 2,010.0 · p50 5.270 / p95 12.743 / p99 17.025 ms	QPS 2,013.0 · p50 5.9 / p95 7.4 / p99 8.1 ms	QPS 3,184.0 · p50 3.7 / p95 5.2 / p99 5.9 ms
Isolated · 1+2-hop neighborhood (N2)	QPS 20,524.4 · p50 0.463 / p95 1.339 / p99 2.035 ms	QPS 14,050.0 · p50 0.8 / p95 1.4 / p99 1.8 ms	QPS 19,369.2 · p50 0.5 / p95 1.2 / p99 1.5 ms
Isolated · shortest path ≤8 (SP)	QPS 25,224.1 · p50 0.314 / p95 1.217 / p99 1.927 ms	QPS 17,338.5 · p50 0.6 / p95 1.1 / p99 1.6 ms	QPS 1,567.8 · p50 7.2 / p95 10.3 / p99 11.7 ms
Isolated · node insert (WN)	QPS 371.1 · p50 18.971 / p95 84.977 / p99 196.899 ms	QPS 8,168.2 · p50 1.4 / p95 2.3 / p99 3.0 ms	QPS 23,875.1 · p50 0.5 / p95 0.8 / p99 1.2 ms
Isolated · property update (U1)	QPS 581.2 · p50 10.021 / p95 89.600 / p99 173.824 ms	QPS 10,563.8 · p50 1.0 / p95 1.9 / p99 2.5 ms	QPS 24,015.9 · p50 0.5 / p95 0.8 / p99 1.2 ms
Isolated · edge mutation (WE)	QPS 310.5 · p50 25.137 / p95 103.591 / p99 262.276 ms	QPS 7,279.8 · p50 1.4 / p95 2.7 / p99 3.4 ms	QPS 24,411.2 · p50 0.4 / p95 0.8 / p99 1.1 ms
30% writes · exact lookup (R1)	QPS 497.1 · p50 1.859 / p95 136.983 / p99 262.718 ms	QPS 13,760.2 · p50 0.6 / p95 2.1 / p99 2.8 ms	QPS 25,644.3 · p50 0.4 / p95 0.8 / p99 1.0 ms
30% writes · age buckets (AG1)	failed · 12 timed errors	QPS 6,124.9 · p50 1.9 / p95 3.3 / p99 4.2 ms	QPS 5,043.2 · p50 2.7 / p95 4.3 / p99 5.7 ms
30% writes · age stats (AG2)	failed · 5 timed errors	QPS 5,712.3 · p50 1.9 / p95 3.7 / p99 4.8 ms	QPS 3,134.0 · p50 4.5 / p95 6.6 / p99 7.7 ms
30% writes · 1-hop expansion (E1)	QPS 628.9 · p50 1.092 / p95 111.119 / p99 206.851 ms	QPS 13,730.3 · p50 0.6 / p95 2.1 / p99 2.8 ms	QPS 24,520.0 · p50 0.4 / p95 0.8 / p99 1.2 ms
30% writes · 2-hop expansion (E2)	QPS 585.5 · p50 1.739 / p95 123.584 / p99 213.858 ms	QPS 12,803.2 · p50 0.7 / p95 2.1 / p99 2.7 ms	QPS 23,270.4 · p50 0.5 / p95 1.0 / p99 1.3 ms
30% writes · 2-hop age filter (E2F)	QPS 562.3 · p50 2.229 / p95 132.204 / p99 174.920 ms	QPS 13,075.3 · p50 0.7 / p95 2.1 / p99 2.7 ms	QPS 23,264.0 · p50 0.5 / p95 0.9 / p99 1.3 ms
30% writes · 3-hop expansion (E3)	QPS 592.0 · p50 2.144 / p95 125.847 / p99 209.276 ms	QPS 10,028.0 · p50 1.2 / p95 1.9 / p99 2.4 ms	QPS 15,912.3 · p50 0.7 / p95 1.4 / p99 1.8 ms
30% writes · 4-hop expansion (E4)	QPS 351.0 · p50 8.038 / p95 146.091 / p99 242.958 ms	QPS 2,741.5 · p50 4.9 / p95 8.8 / p99 10.1 ms	QPS 4,349.5 · p50 3.0 / p95 5.8 / p99 6.9 ms
30% writes · 1+2-hop neighborhood (N2)	QPS 601.1 · p50 1.674 / p95 123.263 / p99 218.567 ms	QPS 12,541.6 · p50 0.7 / p95 2.0 / p99 2.9 ms	QPS 21,662.5 · p50 0.5 / p95 1.1 / p99 1.4 ms
30% writes · shortest path ≤8 (SP)	QPS 578.3 · p50 1.922 / p95 124.862 / p99 208.327 ms	QPS 13,418.7 · p50 0.6 / p95 2.1 / p99 2.8 ms	QPS 2,245.5 · p50 6.4 / p95 8.9 / p99 10.5 ms

Pokec-small read/write mixes

Antfly v0.2.1-rc.3 · bb8a284d

Task	Antfly	Neo4j	Memgraph
Mixed workload · 20/40/10/30 (W1)	failed · 12 timed errors	QPS 9,793.5 · p50 1.0 / p95 2.5 / p99 4.2 ms	QPS 10,980.7 · p50 0.5 / p95 4.1 / p99 5.3 ms
Read-heavy mix · 70/30 (W2)	QPS 672.9 · p50 1.286 / p95 116.357 / p99 223.363 ms	QPS 13,526.5 · p50 0.6 / p95 2.2 / p99 2.9 ms	QPS 25,112.5 · p50 0.4 / p95 0.8 / p99 1.1 ms
Balanced mix · 50/50 (W3)	QPS 528.4 · p50 5.983 / p95 123.558 / p99 229.695 ms	QPS 11,475.3 · p50 0.8 / p95 2.3 / p99 3.1 ms	QPS 24,792.3 · p50 0.4 / p95 0.8 / p99 1.1 ms
Write-heavy mix · 30/70 (W4)	QPS 507.9 · p50 8.695 / p95 120.980 / p99 257.318 ms	QPS 9,782.4 · p50 1.2 / p95 2.4 / p99 3.0 ms	QPS 24,330.4 · p50 0.4 / p95 0.8 / p99 1.1 ms

graph-lsqb-official

partial

Official LSQB

Antfly v0.2.1-rc.3 returned zero q1 matches against eight expected; q2–q9 remain unsupported. Neo4j and Memgraph rows retain earlier correctness results and were not rerun.

Methodology scope · protocol · interpretation

Official LSQB capability and correctness lane

This lane wraps the unmodified LSQB source at commit 62136445b6bc0be8a0ad60ea008b5faa16e34546. It runs the upstream example dataset and hashes the exact cypher/q1.cypher through cypher/q9.cypher files.

Neo4j 5.26.29 and Memgraph 3.12.0 execute each upstream scalar count(*) query. Antfly receives only representable requests. Q1 permits one correctness-only materialization with a preregistered max_results value of 900 when the upstream count falls below that cap. Q2–Q9 receive explicit unsupported classifications; the adapter performs no client-side joins, filtering, or aggregation.

The canonical artifact uses schema graph-lsqb-official-v1, classification capability_matrix, and a complete 27-cell engine/query matrix. It reports no latency, throughput, resource point, or audited LSQB score. Missing cells, upstream validation failures, unexpected unsupported-query requests, or query-file drift fail the artifact. Unsupported cells alone preserve a complete capability result.

Reason provenance is deterministic and requires no agent during a run. Neo4j and Memgraph receive official_scalar_count or upstream_validation_mismatch from direct comparison of the observed count with upstream expected-output.csv. Antfly q2–q9 use the source-controlled UNSUPPORTED mapping in run.py; each entry names the unsupported Cypher shape and the missing scalar aggregation capability, and the harness verifies that no request was issued. That mapping is manually maintained when either the pinned queries or Antfly API capabilities change. A reason entry alone is not sufficient to implement new adapter support: the hashed upstream query and the current Antfly graph API must also be reviewed.

Canonical runs provision their own label-owned dataset volume, Neo4j volume and service, and Memgraph volume and service on the run’s private Docker network. Operator-supplied peer endpoints are not accepted. The official mapping is copied from the unmodified upstream loaders: Comment.csv is labeled Message:Comment, Post.csv is labeled Message:Post, and all 25 relationship files are loaded. The pinned peers are neo4j@sha256:d9dd3dc7d1c78fa959191ff02dbdcbefadceaf83eee23428fb92a58cac8ad3fe (5.26.29) and memgraph/memgraph@sha256:c162cb9a6f76dac6080119da919d9b36e69c8b982af7bf34dd7df2b3723bd69c (3.12.0). Linux/arm64 execution uses the pinned CIRCUS_LINUX_IMAGE runtime.

Every live run retains the asserted Antfly tag, commit, executable SHA-256, query hashes, dataset file hashes and row counts, inspected peer image IDs and repository digests, observed peer versions, exact peer counts, validator output, import logs, query evidence, and service logs. Cleanup stops and removes only containers and volumes carrying both run and benchmark ownership labels, including after import, readiness, validation, or Antfly failure. None of this evidence is a timing sample or resource measurement, and it does not make the lane eligible for an official LSQB score.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: graph-lsqb-official
Domain: official LSQB capability and correctness
Source: https://github.com/ldbc/lsqb
Known Antfly versions: v0.1.3, v0.2.*
Enabled: yes

Benchmark parameters

{"official_score_eligible":false,"operations":[{"correctness":{"actual_count":0,"expected_count":8,"status":"failed"},"engine":"antfly","query_id":"q1","query_sha256":"e08571bf8c877508cd3745ee7dcc8c061259c3b4d5a3fb17a952fbac4f9145ed","reason":"Antfly materialized q1 did not match the upstream scalar count.","reason_code":"upstream_validation_mismatch","request_issued":true,"status":"failed"},{"correctness":{"actual_count":null,"expected_count":3,"status":"not_applicable"},"engine":"antfly","query_id":"q2","query_sha256":"49df895df6b98037f6ce5972d9113ae7a3f263ec009e4fece9ec75bb47410b32","reason":"branch joins and graph_binding_aggregation lack an exact Antfly request","reason_code":"branch_join","request_issued":false,"status":"unsupported"},{"correctness":{"actual_count":null,"expected_count":6,"status":"not_applicable"},"engine":"antfly","query_id":"q3","query_sha256":"5eb0a515fb894e91ecbc1f40656e757884a234953bf87565aec5fcc85007e5be","reason":"multi-pattern cycle joins and graph_binding_aggregation lack an exact Antfly request","reason_code":"multi_pattern_cycle_join","request_issued":false,"status":"unsupported"},{"correctness":{"actual_count":null,"expected_count":8,"status":"not_applicable"},"engine":"antfly","query_id":"q4","query_sha256":"1675c38f7cc117ba9be4de8fc0c1d7073901a03cfc5a174f2241e14c602c9a9f","reason":"branch joins and graph_binding_aggregation lack an exact Antfly request","reason_code":"branch_join","request_issued":false,"status":"unsupported"},{"correctness":{"actual_count":null,"expected_count":3,"status":"not_applicable"},"engine":"antfly","query_id":"q5","query_sha256":"d836a819c7c96819f5dfa14d4e0097bcfb2222eb1561d3ffda22f15067cd8179","reason":"cross-alias predicates and graph_binding_aggregation lack an exact Antfly request","reason_code":"cross_alias_predicate","request_issued":false,"status":"unsupported"},{"correctness":{"actual_count":null,"expected_count":8,"status":"not_applicable"},"engine":"antfly","query_id":"q6","query_sha256":"b8c550aa3c452a99fe65d22ae23e7461ee2705b8be45e96a1d2d1d6143880c93","reason":"cross-alias predicates and graph_binding_aggregation lack an exact Antfly request","reason_code":"cross_alias_predicate","request_issued":false,"status":"unsupported"},{"correctness":{"actual_count":null,"expected_count":11,"status":"not_applicable"},"engine":"antfly","query_id":"q7","query_sha256":"3cb1b31a3f2d05efcaaebaea5ef70231bff30dcfe85aca21cb011ee99175ef0f","reason":"optional matches and graph_binding_aggregation lack an exact Antfly request","reason_code":"optional_match","request_issued":false,"status":"unsupported"},{"correctness":{"actual_count":null,"expected_count":2,"status":"not_applicable"},"engine":"antfly","query_id":"q8","query_sha256":"73fbce9474f0059cfc620c17c5016d19b0974cdbbc8f26637f51b86ea4f24b91","reason":"negative edge predicates and graph_binding_aggregation lack an exact Antfly request","reason_code":"negative_edge_predicate","request_issued":false,"status":"unsupported"},{"correctness":{"actual_count":null,"expected_count":4,"status":"not_applicable"},"engine":"antfly","query_id":"q9","query_sha256":"f0e3402d9bf03cf2e01bf5d812399a4a2f2d40d4558a6ac04d09f0a77afbc8e4","reason":"negative edge predicates and graph_binding_aggregation lack an exact Antfly request","reason_code":"negative_edge_predicate","request_issued":false,"status":"unsupported"}],"scope":"official-query-capability-correctness-only","source_provenance":null,"throughput_score":null}

Peer versions

Peer versions were not recorded in the published result fields.

Evidence digests

Receipt: 4063a2f1deb0f17de5f0444934c35a217b61cd9411bd7932fc37d56d73200419
Aggregate: 95e6c5aca7a38dfbafd071ba9b948dc12d5ddbcb8d4574e51e0f9df743a6bf4a
Provenance: 28a217b486f15bfe36e43c451d283055f1a49aaad705f4e80a29b9e306be4d5f
Harness commit: f4d6b06ddd7ede36a27827d11d653f939a3a2fdb

Selected partial evidence

Completed: 5 Sep 2026 · 15:45 UTC
Antfly: v0.2.1-rc.3 · 4 September 2026 · 03:12 UTC
Runtime: 5.7s
Platform: darwin · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Official query correctness

Antfly v0.2.1-rc.3 · bb8a284d

Query	Engine	Status	Correctness	Request issued	Expected count	Observed count	Reason
q1	antfly	failed	failed	yes	8	0	Antfly materialized q1 did not match the upstream scalar count.
q2	antfly	unsupported	not_applicable	no	3	—	branch joins and graph_binding_aggregation lack an exact Antfly request
q3	antfly	unsupported	not_applicable	no	6	—	multi-pattern cycle joins and graph_binding_aggregation lack an exact Antfly request
q4	antfly	unsupported	not_applicable	no	8	—	branch joins and graph_binding_aggregation lack an exact Antfly request
q5	antfly	unsupported	not_applicable	no	3	—	cross-alias predicates and graph_binding_aggregation lack an exact Antfly request
q6	antfly	unsupported	not_applicable	no	8	—	cross-alias predicates and graph_binding_aggregation lack an exact Antfly request
q7	antfly	unsupported	not_applicable	no	11	—	optional matches and graph_binding_aggregation lack an exact Antfly request
q8	antfly	unsupported	not_applicable	no	2	—	negative edge predicates and graph_binding_aggregation lack an exact Antfly request
q9	antfly	unsupported	not_applicable	no	4	—	negative edge predicates and graph_binding_aggregation lack an exact Antfly request
q1	memgraph	correctness_only	passed	yes	8	8	official_scalar_count: Exact upstream scalar count matched.
q1	neo4j	correctness_only	passed	yes	8	8	official_scalar_count: Exact upstream scalar count matched.
q2	memgraph	correctness_only	passed	yes	3	3	official_scalar_count: Exact upstream scalar count matched.
q2	neo4j	correctness_only	passed	yes	3	3	official_scalar_count: Exact upstream scalar count matched.
q3	memgraph	correctness_only	passed	yes	6	6	official_scalar_count: Exact upstream scalar count matched.
q3	neo4j	correctness_only	passed	yes	6	6	official_scalar_count: Exact upstream scalar count matched.
q4	memgraph	correctness_only	passed	yes	8	8	official_scalar_count: Exact upstream scalar count matched.
q4	neo4j	correctness_only	passed	yes	8	8	official_scalar_count: Exact upstream scalar count matched.
q5	memgraph	correctness_only	passed	yes	3	3	official_scalar_count: Exact upstream scalar count matched.
q5	neo4j	correctness_only	passed	yes	3	3	official_scalar_count: Exact upstream scalar count matched.
q6	memgraph	correctness_only	passed	yes	8	8	official_scalar_count: Exact upstream scalar count matched.
q6	neo4j	correctness_only	passed	yes	8	8	official_scalar_count: Exact upstream scalar count matched.
q7	memgraph	correctness_only	passed	yes	11	11	official_scalar_count: Exact upstream scalar count matched.
q7	neo4j	correctness_only	passed	yes	11	11	official_scalar_count: Exact upstream scalar count matched.
q8	memgraph	correctness_only	passed	yes	2	2	official_scalar_count: Exact upstream scalar count matched.
q8	neo4j	correctness_only	passed	yes	2	2	official_scalar_count: Exact upstream scalar count matched.
q9	memgraph	correctness_only	passed	yes	4	4	official_scalar_count: Exact upstream scalar count matched.
q9	neo4j	correctness_only	passed	yes	4	4	official_scalar_count: Exact upstream scalar count matched.

iii

graph-snb-interactive

partial

SNB Interactive

Antfly v0.2.1-rc.3 qualified four exact read operations; the remaining 25 operations stay unsupported.

Methodology scope · protocol · interpretation

LDBC SNB Interactive v1 bounded read qualification

This incubation lane pins the official Interactive v1.2.0 driver at 4cd13735f964406ad34f34ccd5bef4d6e6c284d0 and Hadoop datagen v1.0.0 at 37d35f40f5023fcf1afd3b6d0984f71c202f4bca. Upstream submodules remain unmodified.

The default gauntlet uses official SF0.1 CsvCompositeMergeForeign-LongDateFormatter data and one fresh Antfly lifecycle. SF1 and SF10 require explicit scale targets. Downloaded or generated data stays under .data/; provenance retains the source URL, archive SHA-256, extracted file manifest, staged node/edge counts, and parameter digest.

The exact qualified subset contains four read operations:

LdbcShortQuery1PersonProfile: versioned Person lookup returning first name, last name, birthday, location IP, browser, city, gender, and creation date;
LdbcShortQuery4MessageContent: versioned Post/Comment lookup returning content-or-image and creation date;
LdbcShortQuery5MessageCreator: exact Message lookup followed by the exact creator Person lookup; both keyed reads contribute to the timed operation; and
LdbcQuery13: unweighted shortest path over KNOWS, returning the path length.

The harness selects deterministic parameters by SHA-256 rank and constructs independent SQLite oracles from the retained CSV files. Every parameter passes exact correctness before timing. Timed records include served-only p50/p95/p99, sample counts, and zero request errors. Result-budget contact, missing parameters, response errors, or oracle mismatches fail the artifact.

All 29 Interactive v1 operations remain visible. Unsupported operations receive explicit semantic reason codes, no request, no fallback, no client-side join/filter/order/aggregation, and no timing. The qualified creator operation uses only its official immutable foreign key for an exact two-key chase. Updates remain unsupported because each official update changes related graph entities or edges atomically.

The canonical artifact uses graph-snb-interactive-v1-qualification-v1, classification partial_read_qualification, and official_score_eligible: false. It does not run the official mixed workload, use official frequencies, report throughput, claim complete conformance, or qualify for public publication. Pinned Neo4j and Memgraph comparison support may follow in a later protocol; this bounded default currently qualifies Antfly against exact official operation semantics.

Run evidence parameters · variation · provenance

Benchmark metadata

Benchmark ID: graph-snb-interactive
Domain: LDBC SNB Interactive v1 partial read qualification
Source: https://github.com/ldbc/ldbc_snb_interactive_v1_driver
Known Antfly versions: v0.1.3, v0.2.*
Enabled: yes

Benchmark parameters

{"official_score_eligible":false,"operations":[{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery1","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_entity_join_and_order","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery2","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_entity_join_and_order","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery3","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"temporal_join_and_aggregation","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery4","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"temporal_join_and_grouping","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery5","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_hop_join_and_grouping","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery6","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_hop_tag_join","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery7","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"negative_edge_predicate_and_order","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery8","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"ordered_reply_join","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery9","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_hop_temporal_order","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery10","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_hop_scoring_and_order","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery11","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_hop_organisation_join","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery12","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_hop_tagclass_join","request_issued":false,"status":"unsupported"},{"correctness":{"exact_parameters":100,"status":"passed"},"engine":"antfly","operation_id":"LdbcQuery13","reason":"Every deterministic parameter matched the independent SQLite oracle.","reason_code":"exact_read_semantics","request_issued":true,"status":"qualified","timing":{"errors":0,"p50_ms":{"median":0.452125,"range":[0.312209,1.617708]},"p95_ms":{"median":1.144167,"range":[0.312209,1.617708]},"p99_ms":{"median":1.523458,"range":[0.312209,1.617708]},"runs":1,"samples":300}},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcQuery14","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"all_shortest_paths_weighted_aggregation","request_issued":false,"status":"unsupported"},{"correctness":{"exact_parameters":100,"status":"passed"},"engine":"antfly","operation_id":"LdbcShortQuery1PersonProfile","reason":"Every deterministic parameter matched the independent SQLite oracle.","reason_code":"exact_read_semantics","request_issued":true,"status":"qualified","timing":{"errors":0,"p50_ms":{"median":0.121667,"range":[0.09175,0.251208]},"p95_ms":{"median":0.1815,"range":[0.09175,0.251208]},"p99_ms":{"median":0.194125,"range":[0.09175,0.251208]},"runs":1,"samples":300}},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcShortQuery2PersonPosts","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"cross_type_union_and_order","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcShortQuery3PersonFriends","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"edge_property_order","request_issued":false,"status":"unsupported"},{"correctness":{"exact_parameters":100,"status":"passed"},"engine":"antfly","operation_id":"LdbcShortQuery4MessageContent","reason":"Every deterministic parameter matched the independent SQLite oracle.","reason_code":"exact_read_semantics","request_issued":true,"status":"qualified","timing":{"errors":0,"p50_ms":{"median":0.3623125,"range":[0.1705,13.980917]},"p95_ms":{"median":0.441167,"range":[0.1705,13.980917]},"p99_ms":{"median":1.196667,"range":[0.1705,13.980917]},"runs":1,"samples":300}},{"correctness":{"exact_parameters":100,"status":"passed"},"engine":"antfly","operation_id":"LdbcShortQuery5MessageCreator","reason":"Every deterministic parameter matched the independent SQLite oracle.","reason_code":"exact_read_semantics","request_issued":true,"status":"qualified","timing":{"errors":0,"p50_ms":{"median":0.5314375,"range":[0.363375,1.756167]},"p95_ms":{"median":0.641208,"range":[0.363375,1.756167]},"p99_ms":{"median":0.773834,"range":[0.363375,1.756167]},"runs":1,"samples":300}},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcShortQuery6MessageForum","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"reply_chain_and_multi_entity_join","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcShortQuery7MessageReplies","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"cross_alias_knows_predicate_and_order","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcUpdate1AddPerson","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_entity_graph_transaction","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcUpdate2AddPostLike","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"edge_transaction","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcUpdate3AddCommentLike","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"edge_transaction","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcUpdate4AddForum","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_entity_graph_transaction","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcUpdate5AddForumMembership","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"edge_transaction","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcUpdate6AddPost","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_entity_graph_transaction","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcUpdate7AddComment","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"multi_entity_graph_transaction","request_issued":false,"status":"unsupported"},{"correctness":{"status":"not_applicable"},"engine":"antfly","operation_id":"LdbcUpdate8AddFriendship","reason":"The exact official operation requires unsupported graph or transaction semantics.","reason_code":"edge_transaction","request_issued":false,"status":"unsupported"}],"scope":"partial_read_qualification","source_provenance":{"datagen":{"commit":"37d35f40f5023fcf1afd3b6d0984f71c202f4bca","serializer":"CsvCompositeMergeForeign-LongDateFormatter","tag":"v1.0.0"},"driver":{"commit":"4cd13735f964406ad34f34ccd5bef4d6e6c284d0","tag":"v1.2.0"},"operation_sha256":{"LdbcQuery13":"8bf956c889992c7508a01196effa2b4eba864421141a99227f384240daffc134","LdbcQuery13Result":"d4cf3752c8639bcffdcdd01a38a9ed8af3ed7cfa5f81792080333f6f5ec5ef26","LdbcShortQuery1PersonProfile":"54e2ace370fbb2f0215b0394e92fcbb3056025fba02f1e25080219d586c913a3","LdbcShortQuery1PersonProfileResult":"f6b7ec32cae1b79bbb538d40a0d8b961729f058b2b6c61d1f08f9ce755544ec0","LdbcShortQuery4MessageContent":"1f544490b719eeddd8f22f264bec82c001c2119ede2a53dd4e1ccbbb5782d2c5","LdbcShortQuery4MessageContentResult":"1a2e471c29d606f7312a7b46e962b28d00dafb3bb6865d14faafc67f419193ba","LdbcShortQuery5MessageCreator":"bc89858d05e70ffbd2719f5ef1518c42d244d89f08459e700d6b6bb51c274a51","LdbcShortQuery5MessageCreatorResult":"97d5d28bf08eb19e684eafe3a785acc8419c487b54aef8c41bbd8078d0f03e4b"},"platform":{"machine":"arm64","system":"darwin"}},"throughput_score":null}

Peer versions

Peer versions were not recorded in the published result fields.

Evidence digests

Receipt: aad504a3743927afb65ad6fe48dd40ca233ecd27b601a5d067249d97226c0111
Aggregate: ef99e7ca0057435ec927d82c63b8e8605df209820b8eb0b270d05a9e23f77786
Provenance: 1e95f32cc4a19ad589a6f43d614902ca645ae182468b2292a775df53531cbbde
Harness commit: f4d6b06ddd7ede36a27827d11d653f939a3a2fdb

Selected partial evidence

Completed: 5 Sep 2026 · 08:15 UTC
Antfly: v0.2.1-rc.3 · 4 September 2026 · 03:12 UTC
Runtime: 1m 01s
Platform: darwin · arm64
Machine: Apple M4 Max
Build: ReleaseFast

Qualified read operations · p95

Antfly v0.2.1-rc.3 (bb8a284d, ReleaseFast/full) · darwin-arm64 · Apple M4 Max · SF0.1 · one lifecycle · zero-error qualified reads

Operation qualification

Antfly v0.2.1-rc.3 · bb8a284d

Operation	Engine	Status	Correctness	Request issued	Reason
LdbcQuery1	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery2	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery3	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery4	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery5	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery6	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery7	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery8	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery9	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery10	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery11	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery12	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcQuery13	antfly	qualified	passed	yes	Every deterministic parameter matched the independent SQLite oracle.
LdbcQuery14	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcShortQuery1PersonProfile	antfly	qualified	passed	yes	Every deterministic parameter matched the independent SQLite oracle.
LdbcShortQuery2PersonPosts	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcShortQuery3PersonFriends	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcShortQuery4MessageContent	antfly	qualified	passed	yes	Every deterministic parameter matched the independent SQLite oracle.
LdbcShortQuery5MessageCreator	antfly	qualified	passed	yes	Every deterministic parameter matched the independent SQLite oracle.
LdbcShortQuery6MessageForum	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcShortQuery7MessageReplies	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcUpdate1AddPerson	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcUpdate2AddPostLike	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcUpdate3AddCommentLike	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcUpdate4AddForum	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcUpdate5AddForumMembership	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcUpdate6AddPost	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcUpdate7AddComment	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.
LdbcUpdate8AddFriendship	antfly	unsupported	not_applicable	no	The exact official operation requires unsupported graph or transaction semantics.

XII

5 lanes without selected evidence

Missing evidence

document-omnidocbench

missing

OmniDocBench

Document parsing and structure-recovery quality across the OmniDocBench evaluation surface.

Methodology scope · protocol · interpretation

OmniDocBench Methodology

benchmarks/OmniDocBench is the raw benchmark checkout and stays pointed at the Antfly-owned OmniDocBench origin. This harness directory contains antfly-circus-specific adapter code, methodology notes, generated prediction directories, and OmniDocBench evaluator outputs.

Measurement surface

OmniDocBench measures document parsing quality, not plain OCR alone. Each engine must produce one markdown prediction per page; OmniDocBench then scores text recognition, table reconstruction, formula rendering, and reading order.

Antfly is invoked through the central Bastille handoff: antfly-circus passes the exact benchmark binary as ANTFLY_BIN, and the adapter only consumes that binary. It does not discover or substitute another Antfly executable.

Default smoke profile

Dataset: OmniDocBench demo data
Prediction format: one markdown file per page
Evaluation: OmniDocBench end2end config shape
Smoke behavior: verify adapter wiring and output paths without claiming full OmniDocBench leaderboard coverage

Full benchmark profile

The default full profile runs --engine antfly --protocol page-image over the bundled OmniDocBench demo subset: 18 page images. It writes one Antfly-generated markdown prediction per page, evaluates with OmniDocBench, and reports quality metrics first: Overall, text edit distance, table TEDS, formula CDM, and reading-order edit distance. Prediction throughput is reported separately as pages/s.

Set ANTFLY_DOC_MODEL_DIR to the explicit reader model directory and ANTFLY_BIN to the exact Antfly binary under test. The adapter intentionally does not substitute bundled demo predictions for missing Antfly output.

Protocols and peers

page-image: runnable with the bundled demo data. Engines receive raster page images and must emit markdown files whose names match the OmniDocBench image stems.
native-pdf: dataset/API-gated. It is blocked unless PDF inputs and a compatible native-PDF engine path are configured. The adapter does not silently rasterize PDFs and call that native PDF parsing.

Open-source peer rows are wrapper-based. Configure command templates with OMNIDOCBENCH_MINERU_CMD, OMNIDOCBENCH_MARKER_CMD, OMNIDOCBENCH_DOCLING_CMD, or OMNIDOCBENCH_OCR_BASELINE_CMD. Templates may use {input}, {output}, {output_dir}, and {stem} placeholders. The OCR-only baseline can also use TESSERACT_BIN or tesseract on PATH.

Record the exact image/PDF input set, command template or Antfly command, model directory/backend selected, protocol, worker counts, whether CDM is enabled, and all generated OmniDocBench result JSON files under benchmarks/OmniDocBench-harness/result. The full 1651-page OmniDocBench dataset is not bundled in this checkout; pull it from the upstream Hugging Face/OpenDataLab dataset before reporting full benchmark coverage.

Evidence status availability · expected contract

Benchmark metadata

Benchmark ID: document-omnidocbench
Domain: document pipeline
Source: https://github.com/opendatalab/OmniDocBench
Known Antfly versions: v0.2.*
Enabled: yes

Why this lane has no selected measurement

No reviewed benchmark result is selected for this subject.

Expected: Reviewed aggregate with a validation receipt
Observed: No result selected for this subject

rag-mtcb

missing

MTCB

Chunking and retrieval behavior measured through the MTCB Antfly benchmark.

Methodology scope · protocol · interpretation

MTCB Antfly Benchmark

MTCB evaluates retrieval quality for chunked RAG corpora. The upstream harness chunks documents, embeds chunks and questions, retrieves top-k chunks, and scores whether the gold passage appears in the retrieved chunk set.

Antfly Surface

This adapter keeps MTCB’s evaluator and metric calculations, but replaces the in-memory vector store with Antfly external-vector retrieval:

one Antfly table per MTCB dataset evaluator;
one external aknn_v0 cosine vector index named vec;
chunk text is stored as table metadata and the vector is inserted in _embeddings.vec;
queries use /api/v1/query with embeddings.vec and the requested limit.

The adapter uses local deterministic lexical hashing embeddings by default. This keeps the benchmark self-contained and avoids depending on hosted embedding APIs. The result is therefore a benchmark of Antfly storage/index/query behavior inside MTCB’s scoring loop, not a claim about a production embedding model.

Profiles

smoke: one nano dataset, currently nano-macha, intended to validate adapter wiring and artifact shape.
nano / honed: three nano datasets, currently nano-macha, nano-sencha, and nano-hojicha, intended to produce a small but real retrieval result.

The adapter reports Recall@k, Precision@k, MRR@k, and NDCG@k for each dataset, plus mean metrics across datasets. It also recomputes mean Recall@k from the per-dataset rows and marks the run failed if the recomputed value diverges from MTCB’s BenchmarkResult.

Runtime Pin

The benchmark should be run against Antfly 0.2.0-rc.17 for the current Bastille result. The run artifact records the Antfly URL and best-effort runtime version endpoint response. The local harness can use ANTFLY_BIN to point at a specific prebuilt runtime; no Zig build should be triggered by this benchmark.

Caveats

MTCB’s public examples usually use neural embedding models such as Voyage. The current Antfly adapter deliberately uses local hashing embeddings to make the benchmark repeatable without credentials or model downloads. Before making a leaderboard-style quality claim, rerun the adapter with a documented production embedding model and compare against MTCB’s original in-memory vector store using the same chunks and embeddings.

Evidence status availability · expected contract

Benchmark metadata

Benchmark ID: rag-mtcb
Domain: rag/chunking
Source: https://github.com/feyninc/mtcb
Known Antfly versions: v0.2.0-rc.18
Enabled: yes

Why this lane has no selected measurement

No reviewed benchmark result is selected for this subject.

Expected: Reviewed aggregate with a validation receipt
Observed: No result selected for this subject

iii

rag-browsecomp-plus

missing

BrowseComp Plus

Fixed-budget native-hybrid retrieval over the BrowseComp-Plus evaluation set.

Methodology scope · protocol · interpretation

Agent Retrieval Cost harness

Measures what it actually costs an agent to answer questions over a large fixed corpus with different retrieval tooling. Quality (answer accuracy) is reported alongside cost; cost is the story: total LLM tokens, USD, wall time, and tool calls per query.

BrowseComp-Plus native-hybrid honed lane

bcp_native_hybrid/ is the publication lane for the four existing products that expose a genuinely native hybrid request: Antfly, Elasticsearch, Weaviate, and Milvus. PgVector and Chroma are excluded because their current harness paths are dense-only; adding those paths would change the retrieval contract. The separate lexical/TREC adapter is diagnostic and is not consumed by the publication page.

The checked bcp_native_hybrid/panel.json freezes 50 seed-17 development queries and their disjoint 780-query complement. The development panel is used only to warm memory lifecycles. Luna, through pinned pi 0.73.1, answers every held-out query against every backend: 3,120 evaluated query cells. Each cell uses the official Qwen3-Embedding-8B vectors and query prefix, the upstream QUERY_TEMPLATE_NO_GET_DOCUMENT, one search(query) tool, top five results, 512 Qwen3-0.6B snippet tokens, and the checked turn/token ceilings. Harbor supervises the Luna process without adding shell, filesystem, browser, or document-fetch tools.

Query publication evidence is resumed one backend/query cell at a time through the generic Circus publication cache. An exact hit includes the normalized trajectory, raw pi trajectory and stderr, Luna final record, Harbor result, complete Qwen3-32B judgement, original timestamps, and receipt. Corpus, vector, prompt, client, model, judge, backend, and Antfly-subject identities are part of the key. Incorrect answers and complete no-search outcomes are measured evidence; no-search always forces protocol correctness false. Crashes, partial trajectories, missing or unparseable judgements, and setup failures never hit. Database volumes, indexes, downloads, and memory measurements are never cached. First qualifying cache evidence wins under the generic cache policy. Fresh promotion also requires the operator’s explicit CIRCUS_QUIET_HOST_READY=1 assertion, retained as quiet-host.json.

The checked four-shard Latin-square schedule gives each backend every execution position once while still running all 780 held-out queries per backend. Only one backend stack is resident at a time. Every backend also receives exactly three deliberately fresh cgroup-v2 whole-stack memory lifecycles. Sampling starts before launch and covers prelaunch, service-launch, ingest, readiness, warm-query, and post-warm-idle. Publication memory is the warm-query anon + shmem peak mean and range; lifecycle demand, memory.current, kernel peaks, disk, events, images, logs, and raw timelines remain retained diagnostics. Swap, failed samples, incomplete phases, reused storage, or fewer than three trials rejects the report.

The report publishes per-backend correct count, accuracy with Wilson 95% interval, evidence recall, search/input/total-token distributions, completion, zero-search, and cached/fresh counts. Antfly-minus-peer paired accuracy and evidence-recall differences use the named paired-score mean ± 1.959963984540054 standard-error interval. These intervals are descriptive; no comparative acceptance threshold or automatic editorial selection is applied. Agent and judge wall time is network-bound diagnostic telemetry, not a latency claim.

From the repository root:

make browsecomp-native-hybrid-prepare
make browsecomp-native-hybrid-smoke
make browsecomp-native-hybrid-honed
make browsecomp-native-hybrid-report

The honed command writes strict summary.json, summary.md, detailed.json, raw runs/evals, cache references, memory timelines, and receipt.json to $BASTILLE_OUT/data/rag-browsecomp-plus/.

Design: trust through off-the-shelf parts

Agent: pi, an independent off-the-shelf coding agent (tools: read/write/edit/bash), run headless.
Orchestration: Harbor (the Terminal-Bench 2.0 harness, pinned version in the root Makefile) using Harbor’s first-party pi agent adapter (harbor run -a pi).
Antfly authors only the environments and the report. There is no bespoke agent loop; per-query tokens and USD cost come from pi’s own session accounting (message_end usage events in /logs/agent/pi.txt), parsed the same way Harbor itself does, not from our instrumentation.

One Harbor task per (tooling x question); one pi session per question; session totals are the per-query metrics.

Dataset

BrowseComp-Plus (Tevatron/browsecomp-plus): 100,195-document corpus, 830 queries with gold answers, cached at .data/browsecomp-plus/ by the BrowseComp-Plus harness. Questions are deliberately hard deep-research puzzles; absolute accuracy is expected to be low for every tooling. v1 applies no quality bar — accuracy is reported next to cost.

Fairness rules

Same questions for every tooling: one seed-17 pool of 200 query ids, sampled once; every run size is a prefix (probe 10 ⊂ default 50 ⊂ publish 200).
Same corpus surface: identical document text, capped at ARC_DOC_CHARS (default 20,000 chars/doc), in every store.
Same agent, same model (default openai-codex/gpt-5.6-luna, run on a ChatGPT subscription), same instruction contract; only the tooling cheat-sheet section differs.
Setup is performed by the harness, deterministically, before agent runs; setup wall time is reported in its own table and never billed to per-query cost. (Agent-performed setup is the separate agent-effort suite.)
The judge (default openai/gpt-4.1, same prompt as the BrowseComp-Plus answer eval) grades answers offline; judge spend is reported separately and never added to a row’s cost. Failed/unanswered queries count as incorrect.
Egress is audited, not firewalled: pi needs openrouter.ai, so containers have network access. The instruction forbids internet use, pi has no web tool, and the harvester scans every bash tool call for non-local hosts and flags suspect_egress per record (surfaced in the run-health table). A proxy allowlist is future work.

Toolings

Row	Surface in the container
grep	raw corpus as 100 JSONL shards at `/corpus/`, ripgrep installed
sqlite	prebuilt FTS5 database at `/corpus/corpus.fts5.db`, sqlite3 CLI
antfly	HTTP endpoint (host `make start-zig`, port 28080), BM25 full-text table
elasticsearch	HTTP endpoint (`elasticsearch_bench` container), BM25 index
pgvector / milvus / weaviate / chroma	vector search over shared bge-small-en-v1.5 embeddings + a query-time embed endpoint (phase 3)

Running

Everything is driven from the repo root Makefile:

make agent-retrieval-cost-setup    # venv + harbor patch + base images + ingest (timed)
make agent-retrieval-cost-smoke    # free, offline: templates + parser fixture + report
make agent-retrieval-cost-probe    # paid: 10 questions x grep,sqlite,antfly
make agent-retrieval-cost-honed    # paid: ARC_SAMPLE (50) x ARC_TOOLINGS
make agent-retrieval-cost-judge    # paid: offline judge pass over harvested records
make agent-retrieval-cost-report   # free: agent-summary.json + summary.md

Knobs: ARC_MODEL, ARC_JUDGE_MODEL, ARC_SAMPLE, ARC_TOOLINGS, ARC_CONCURRENCY, ARC_ROW_CONCURRENCY, ARC_DOC_CHARS, ARC_AGENT_TIMEOUT (uniform per-task agent timeout, default 1800 s — the same for every tooling so wall/cost comparisons stay fair), ARC_RUN_ID. The OpenRouter key (used by the offline judge) is read from the process environment, the legacy agent_retrieval_cost.env, or pi’s private ~/.pi/agent/auth.json. The key is never copied into the repository.

Full 830-question checkpointed run

The full lane uses the seven validated surfaces (grep, sqlite, antfly, elasticsearch, pgvector, chroma, and antfly_hybrid) and the pinned v0.2.0-rc.20 ReleaseFast subject manifest. It is cohort-driven: 33 cohorts contain 25 questions and the final cohort contains five. Every cohort is paired across all seven rows, and one command invocation runs at most one cohort.

make agent-retrieval-cost-full-prepare  # dataset, stores, immutable manifest
make agent-retrieval-cost-full-canary   # one question x seven rows
make agent-retrieval-cost-full-next     # one 25-question paired cohort
make agent-retrieval-cost-full-drain    # repeat cohorts; stop on first safety pause
make agent-retrieval-cost-full-status   # no model calls

full-drain is only a checkpoint supervisor: it invokes the same one-cohort lane repeatedly, reruns every preflight before advancing, and exits immediately if an attempt is paused or fails. It does not weaken the per-cohort cost, auth, disk, service, or retry protections.

full-run-manifest.json freezes question order, cohort boundaries, models, toolings, and subject hashes. full-run-ledger.json records immutable attempts. Harvest merges by (tooling, query_id), refuses to overwrite a final cell, and only replaces explicit authentication, rate-limit, or infrastructure failures. Completed cells therefore survive an outage and are skipped on resume.

The preflight requires all stores to report 100,195 indexed documents, a ready and fully query-visible Antfly vector index, at least 30 GB free, and at least two hours of OAuth validity. It warns at $550 and refuses to launch a new cohort at $650 of API-equivalent Luna usage. The incremental OpenRouter judge has a separate $5 actual-spend hard cap. Subscription agent spend remains $0 incremental; equivalent cost is an analysis yardstick, not a cash charge.

Partial reports contain only fully paired questions. Reports include the accuracy-vs-budget curve with bootstrap intervals, a cost-vs-quality scatter/Pareto chart, cost per correct answer, payload volume, command errors, and evidence-to-first-hit diagnostics. Raw de-obfuscated questions and document content remain local and must not be pasted into public summaries.

Rows run through a bounded scheduler. The default is two Harbor rows in parallel (ARC_ROW_CONCURRENCY=2), with four concurrent trials in each row (ARC_CONCURRENCY=4): at most eight subscription agents at once. The 50×7 RF335 run’s observed row durations project to roughly 95 minutes of inference at this setting instead of 172 minutes sequentially. Parallel rows share host resources, so wall-time comparisons should be treated as contention-sensitive; token, cost, and accuracy metrics remain per isolated trial. Set ARC_ROW_CONCURRENCY=1 to reproduce the old sequential schedule.

Model auth

The agent model defaults to openai-codex/gpt-5.6-luna — GPT-5.6 Luna run on a ChatGPT Plus/Pro subscription via pi’s Codex OAuth provider. One-time setup: run pi interactively, /login, and pick “ChatGPT Plus/Pro (Codex)” to complete the browser OAuth. That writes ~/.pi/agent/auth.json, which the harness bind-mounts read-only into every trial container (--mounts). The run preflight refuses to start if that file is empty.

Because a subscription is flat-rate, pi reports token counts but $0 cost, so $/query is computed from token counts at published Luna rates ($1/$6/$0.10 per 1M in/out/cached-read) and each record is tagged cost_source: price_table_estimate. See arc/pricing.py. Pass a different ARC_MODEL (e.g. openai/gpt-5.6-luna with OPENAI_API_KEY, or openrouter/...) to use real per-token billing instead; pi’s own cost_usd is then used and tagged pi_usage.

Note: Codex OAuth access tokens expire in hours. For long matrix runs, log in (or refresh) shortly before starting; the read-only mount can’t refresh mid-run.

Outputs

Under $BASTILLE_OUT/data/agent-retrieval-cost/:

<tooling>/records.jsonl — one record per (tooling, query): status, answer, gold, tokens {input, output, cache_read, cache_write, total}, cost_usd (pi’s own accounting), wall_seconds (first-to-last session event; excludes image build and pi install), tool_calls, suspect_egress, judge verdict.
agent-summary.json, setup-summary.json, judge-summary.json, summary.md (per-query means, setup table, cumulative cost, run health).

Caveats

Wall/query depends on host load and provider latency at run time; treat it as indicative, not a latency benchmark.
Timed-out and provider-errored trials (e.g. OpenRouter routes occasionally return content_filter mid-run) count as incorrect and stay in the denominator; the run-health table reports them per row.
pi is installed per trial by Harbor’s adapter (npm install -g ...@latest); the base image pre-installs node+pi so this is fast, but pi’s version floats with the run date and is recorded in /etc/arc-pi-version in the image.
Harbor’s old upload_dir docker-cp bug (verifier tests landing at /tests/tests/) is fixed upstream in the pinned version; patches/apply_harbor_upload_dir_patch.py verifies this and can patch the legacy layout if the pin ever moves backwards.
Vector rows share one embedding model and code path (ingest == query-time); engines’ native embedding pipelines are intentionally not used.

Evidence status availability · expected contract

Benchmark metadata

Benchmark ID: rag-browsecomp-plus
Domain: rag/fixed-budget-retrieval
Source: https://github.com/texttron/BrowseComp-Plus
Known Antfly versions: v0.2.*
Enabled: yes

Why this lane has no selected measurement

No reviewed benchmark result is selected for this subject.

Expected: Reviewed aggregate with a validation receipt
Observed: No result selected for this subject

agent-retrieval-cost

missing

Agent retrieval cost

Retrieval quality and resource cost for agent-oriented search workflows.

Methodology scope · protocol · interpretation

Agent Retrieval Cost harness

BrowseComp-Plus native-hybrid honed lane

From the repository root:

make browsecomp-native-hybrid-prepare
make browsecomp-native-hybrid-smoke
make browsecomp-native-hybrid-honed
make browsecomp-native-hybrid-report

The honed command writes strict summary.json, summary.md, detailed.json, raw runs/evals, cache references, memory timelines, and receipt.json to $BASTILLE_OUT/data/rag-browsecomp-plus/.

Design: trust through off-the-shelf parts

Agent: pi, an independent off-the-shelf coding agent (tools: read/write/edit/bash), run headless.
Orchestration: Harbor (the Terminal-Bench 2.0 harness, pinned version in the root Makefile) using Harbor’s first-party pi agent adapter (harbor run -a pi).
Antfly authors only the environments and the report. There is no bespoke agent loop; per-query tokens and USD cost come from pi’s own session accounting (message_end usage events in /logs/agent/pi.txt), parsed the same way Harbor itself does, not from our instrumentation.

One Harbor task per (tooling x question); one pi session per question; session totals are the per-query metrics.

Dataset

Fairness rules

Same questions for every tooling: one seed-17 pool of 200 query ids, sampled once; every run size is a prefix (probe 10 ⊂ default 50 ⊂ publish 200).
Same corpus surface: identical document text, capped at ARC_DOC_CHARS (default 20,000 chars/doc), in every store.
Same agent, same model (default openai-codex/gpt-5.6-luna, run on a ChatGPT subscription), same instruction contract; only the tooling cheat-sheet section differs.
Setup is performed by the harness, deterministically, before agent runs; setup wall time is reported in its own table and never billed to per-query cost. (Agent-performed setup is the separate agent-effort suite.)
The judge (default openai/gpt-4.1, same prompt as the BrowseComp-Plus answer eval) grades answers offline; judge spend is reported separately and never added to a row’s cost. Failed/unanswered queries count as incorrect.
Egress is audited, not firewalled: pi needs openrouter.ai, so containers have network access. The instruction forbids internet use, pi has no web tool, and the harvester scans every bash tool call for non-local hosts and flags suspect_egress per record (surfaced in the run-health table). A proxy allowlist is future work.

Toolings

Row	Surface in the container
grep	raw corpus as 100 JSONL shards at `/corpus/`, ripgrep installed
sqlite	prebuilt FTS5 database at `/corpus/corpus.fts5.db`, sqlite3 CLI
antfly	HTTP endpoint (host `make start-zig`, port 28080), BM25 full-text table
elasticsearch	HTTP endpoint (`elasticsearch_bench` container), BM25 index
pgvector / milvus / weaviate / chroma	vector search over shared bge-small-en-v1.5 embeddings + a query-time embed endpoint (phase 3)

Running

Everything is driven from the repo root Makefile:

make agent-retrieval-cost-setup    # venv + harbor patch + base images + ingest (timed)
make agent-retrieval-cost-smoke    # free, offline: templates + parser fixture + report
make agent-retrieval-cost-probe    # paid: 10 questions x grep,sqlite,antfly
make agent-retrieval-cost-honed    # paid: ARC_SAMPLE (50) x ARC_TOOLINGS
make agent-retrieval-cost-judge    # paid: offline judge pass over harvested records
make agent-retrieval-cost-report   # free: agent-summary.json + summary.md

Full 830-question checkpointed run

make agent-retrieval-cost-full-prepare  # dataset, stores, immutable manifest
make agent-retrieval-cost-full-canary   # one question x seven rows
make agent-retrieval-cost-full-next     # one 25-question paired cohort
make agent-retrieval-cost-full-drain    # repeat cohorts; stop on first safety pause
make agent-retrieval-cost-full-status   # no model calls

Model auth

Note: Codex OAuth access tokens expire in hours. For long matrix runs, log in (or refresh) shortly before starting; the read-only mount can’t refresh mid-run.

Outputs

Under $BASTILLE_OUT/data/agent-retrieval-cost/:

<tooling>/records.jsonl — one record per (tooling, query): status, answer, gold, tokens {input, output, cache_read, cache_write, total}, cost_usd (pi’s own accounting), wall_seconds (first-to-last session event; excludes image build and pi install), tool_calls, suspect_egress, judge verdict.
agent-summary.json, setup-summary.json, judge-summary.json, summary.md (per-query means, setup table, cumulative cost, run health).

Caveats

Wall/query depends on host load and provider latency at run time; treat it as indicative, not a latency benchmark.
Timed-out and provider-errored trials (e.g. OpenRouter routes occasionally return content_filter mid-run) count as incorrect and stay in the denominator; the run-health table reports them per row.
pi is installed per trial by Harbor’s adapter (npm install -g ...@latest); the base image pre-installs node+pi so this is fast, but pi’s version floats with the run date and is recorded in /etc/arc-pi-version in the image.
Harbor’s old upload_dir docker-cp bug (verifier tests landing at /tests/tests/) is fixed upstream in the pinned version; patches/apply_harbor_upload_dir_patch.py verifies this and can patch the legacy layout if the pin ever moves backwards.
Vector rows share one embedding model and code path (ingest == query-time); engines’ native embedding pipelines are intentionally not used.

Evidence status availability · expected contract

Benchmark metadata

Benchmark ID: agent-retrieval-cost
Domain: agents/retrieval-cost
Source: https://github.com/badlogic/pi-mono
Known Antfly versions: v0.2.*
Enabled: yes

Why this lane has no selected measurement

No reviewed benchmark result is selected for this subject.

Expected: Reviewed aggregate with a validation receipt
Observed: No result selected for this subject

office-qa-pro

missing

OfficeQA Pro

Raw-document ingestion, retrieval, and question answering over the OfficeQA-Pro corpus.

Methodology scope · protocol · interpretation

OfficeQA-Pro raw-PDF benchmark

This harness measures the complete path from 697 Treasury Bulletin PDFs to an agent’s final answer. The headline comparison is ingestion complexity and cold setup time; answer accuracy and agent cost are measured on the same seeded OfficeQA-Pro questions after each index is ready.

The default matrix is 133 questions per row with seed 17:

Row	Source	Extraction and retrieval
`antfly_native_hybrid`	Raw PDFs	Antfly PDF extraction/OCR, chunking, embedding, lexical + vector index
`docling_pgvector`	Raw PDFs	Docling standard OCR + accurate tables, BGE chunks/embeddings, pgvector HNSW
`docling_elasticsearch`	Raw PDFs	The same Docling chunks, Elasticsearch BM25
`docling_sqlite`	Raw PDFs	The same Docling chunks, SQLite FTS5
`oracle_pgvector`	Publisher transformed text	Clearly labeled extraction ceiling, BGE + pgvector HNSW

The three Docling rows share one extraction pass. The oracle files never enter a raw-PDF row. Questions given to agents contain neither source_files hints nor gold answers.

Prerequisites

Docker, uv, Go, and enough disk for the 4 GB corpus plus derived indexes.
Hugging Face access accepted for the gated databricks/officeqa dataset and HF_TOKEN exported for the explicit download step.
pi logged into ChatGPT (pi, then /login) for the default openai-codex/gpt-5.6-luna agent.
A ReleaseFast Antfly binary. Override the suite default with ANTFLY_BIN=/absolute/path/to/antfly.

The Antfly qualification deliberately includes one scanned and one born-digital PDF. Run it before committing to the corpus-wide ingest. Current Antfly source needs to render the requested PDF page to PNG before sending it to the local Florence reader; passing the PDF URL directly is not supported by that reader. docsaf sync --help also needs to show the --ocr* options.

Only rebuild Antfly after checking those help texts and qualifying the binary. On this machine a full Zig build may run out of memory, so warn and get explicit approval first, then constrain parallelism:

cd /path/to/antfly/zig
zig build lib-pdf-test -j1
zig build lib-db-test -j1 -- --test-filter 'document OCR media parts'
zig build install -Dedition=full -Doptimize=ReleaseFast -j1

Run sequence

make targets live at the antfly-circus repository root.

make office-qa-pro-smoke
make office-qa-pro-setup
make office-qa-pro-download

# Before the large ingest:
ANTFLY_BIN=/path/to/antfly make office-qa-pro-qualify-antfly

# Paid 10-question, three-row end-to-end probe:
ANTFLY_BIN=/path/to/antfly make office-qa-pro-probe

# Paid Pro-133, five-row matrix:
ANTFLY_BIN=/path/to/antfly make office-qa-pro-honed

office-qa-pro-honed refuses to download data implicitly. It starts only the services selected by OQA_TOOLINGS, performs a cold setup, generates identical seeded tasks, runs Harbor/pi at OQA_CONCURRENCY=4, harvests, deterministically scores, and writes the report. Useful overrides include:

make office-qa-pro-honed \
  OQA_SAMPLE=20 \
  OQA_TOOLINGS=docling_pgvector,docling_sqlite \
  OQA_CONCURRENCY=2

Measurement and scoring

Downloads and model-cache warmup are excluded from setup timing. Setup begins with local source files and cached models; each recorded stage and total wall time is written to setup-summary.json. The raw-PDF rows include extraction, OCR, chunking, embedding where applicable, and indexing.

The scorer is reward.py pinned to OfficeQA commit 86753108d69e149cc28abd346bb8c3ca1cbfc7cf. It is applied to the final answer and every running best guess at exact, 0.1%, 1%, and 5% relative tolerance. The primary metric is accuracy at 1%; no LLM judge is used.

Agent accounting is inherited from the ARC harness: input/cache/output tokens, price-table-equivalent USD, wall time, tool calls, answer trajectory, and cost to the first answer that remains correct. Results land under results/benchmark-page/manual/data/office-qa-pro/ by default.

Planning estimate

The full default run is 665 trials (133 questions × 5 rows). Existing local ARC Luna trials average about $0.42 price-table-equivalent and 138 seconds of total trial wall time. That gives a lower-bound query phase of roughly $280 and 6.4 hours at concurrency four. OfficeQA is likely to require longer investigation, so budget approximately $300–$600 equivalent and 7–12 hours for agent trials. The default model uses a ChatGPT subscription, so this is benchmark accounting, not necessarily an incremental API invoice, but it will consume subscription capacity.

The larger uncertainty is cold ingestion of about 89,000 PDF pages with CPU/local ML OCR. Until the two-PDF qualification and a small corpus timing are measured, allow roughly 2–6 elapsed days end to end, of which most is Antfly and Docling extraction/OCR. The 10-question probe should be used to replace this range with measured throughput before launching Pro-133.

Evidence status availability · expected contract

Benchmark metadata

Benchmark ID: office-qa-pro
Domain: agents/raw-document-ingestion
Source: https://github.com/databricks/officeqa
Known Antfly versions: v0.2.*
Enabled: yes

Why this lane has no selected measurement

No reviewed benchmark result is selected for this subject.

Expected: Reviewed aggregate with a validation receipt
Observed: No result selected for this subject

VIII

1 of 1 lane measured

End-to-end

Agent-facing product activation and first retrieval from clean interactive Pi sessions.

quickstart-first-retrieval

partial

Quickstart

11 database-version rows retain every recording. Median time summarizes observed retrievals; validation reports which sessions completed cleanly.

Database	Version	Median time	Validation	Sessions
Antfly	v0.1.3	228.554 s	passed	Watch sessions 1
Antfly	v0.2.0	228.262 s	passed	Watch sessions 1 2
Antfly	v0.2.1-rc1	111.846 s	passed	Watch sessions 1 2 3
Chroma	v1.5.9	79.072 s	passed	Watch sessions 1
Elasticsearch	v9.5.2	445.708 s	passed	Watch sessions 1
Memgraph	v3.12.0	67.161 s	passed	Watch sessions 1
Milvus Lite	v3.0.1	198.412 s	passed	Watch sessions 1
Neo4j	v2026.07.1	60.369 s	passed	Watch sessions 1
Quickwit	v0.9.0	61.978 s	passed	Watch sessions 1
Weaviate	v1.39.2	228.033 s	passed	Watch sessions 1
Antfly	v0.2.1	32.093 s	partial · 2/3 valid	Watch sessions 1 2 3

Methodology Timing · grouping · validation

Timing boundary

Time to first retrieval runs from PTY capture start through the first successful qualifying search result observed in the Pi session. Acquisition, installation, setup, retries, and agent reasoning all contribute to elapsed time.

Grouping and median

Each row groups retained sessions by database and exact observed version. The median includes every observed qualifying retrieval, including a retrieval followed by failed post-session verification. Validation remains separate. Models and task boundaries can differ between cohorts; these rows are not controlled product-speed comparisons.

Protocol history

Historical Antfly recordings use protocol 3 and its qualifying retrieval command. New natural recordings use protocol 4 passive Pi result correlation, without an agent-visible marker. Container-dependent sessions substitute rootless Podman for Docker and retain that runtime choice in provenance. Numbered session links preserve the full trajectory and protocol evidence behind every row.

Container boundary

Container-dependent sessions use an operator-approved rootless Podman host-user API. Bubblewrap limits the agent shell but does not constrain bind mounts requested through that API. The runner snapshots preexisting Podman resources, restricts verification to containers created by the attempt, removes attempt-owned resources afterward, scans published transcripts for credentials, and records the socket scope in provenance.

Validation states

Passed: Every included session produced a qualifying retrieval and passed its retained verifier.
Partial: At least one included session passed while another lacked complete valid evidence.
Failed: Included sessions completed without a qualifying verified retrieval.
Unverified: Retained evidence lacks a terminal verifier result.

Three fresh sequential v0.2.1 sessions used OpenRouter GLM-5.3 Flash with high thinking, host CPUs, and an explicit hello/first stopping objective. All three produced the expected retrieval; two passed post-session verification. Trial 2 shut down Antfly afterward, causing ConnectionRefused. Median includes all three observed retrievals, not just verified sessions. Release and prompt differ from earlier cohorts; this is not an isolated product speed comparison. Model installation, semantic search and RAG were not exercised.