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Cohere-100M — 2026-07-07

r8i.24xlarge · peak recall 0.9872 @ 59 QPS

QPS at recall

RecallMeerkatpgvector HNSW (halfvec)pgvector HNSW (bit)Δ vs best competitor
0.90427270— (min r=0.947)+58%
0.95207130— (max r=0.950)+60%

Latency at recall

Meerkatpgvector HNSW (halfvec)pgvector HNSW (bit)Δ vs best competitor
@ recall 0.90
p502.32 ms3.74 ms—-38%
p952.88 ms5.00 ms—-42%
p993.16 ms6.04 ms—-48%
@ recall 0.95
p504.77 ms8.00 ms—-40%
p955.90 ms9.83 ms—-40%
p996.46 ms10.87 ms—-41%

All values are taken at exactly the stated recall: each configuration's own sweep is log-interpolated between its two surrounding measured points (measured values are used verbatim on an exact hit) and the best configuration at that recall is shown — values are never interpolated across different configurations. “—” means no single sweep spans that recall; nothing is extrapolated. Recall is distance-based (ann-benchmarks, tie-aware). Insert/update/delete workloads are not measured.

Interpolated on config — Meerkat @0.90: mkt-n400000-cctrue-fs16-soar-cfs · pgvector HNSW (halfvec) @0.90: hnsw-m24-halfvec · Meerkat @0.95: mkt-n400000-cctrue-fs16-soar-cfs · pgvector HNSW (halfvec) @0.95: hnsw-m24-halfvec

Build comparison

Meerkatpgvector HNSW (halfvec)pgvector HNSW (bit)Δ vs best competitor
Build time37917 s22012 s—+72%
Index size20.9 GB179.2 GB—-88%

Build stats are for the configuration backing each column's best operating point: Meerkat = mkt-n400000-cctrue-fs16-soar-cfs · pgvector HNSW (halfvec) = hnsw-m24-halfvec.

Plots

Pareto svg  ·  Distance-recall svg  ·  Per-config svg  ·  Build times svg  ·  Index sizes svg
paretodistance-recallbuild-timesbuild-sizes

Host

Instance typer8i.24xlarge
Hostnameip-172-31-66-31
CPUIntel(R) Xeon(R) 6975P-C (96 vCPU)
Memory744 GB
OSUbuntu 26.04 LTS
Kernel7.0.0-1008-aws

Versions

rekall0.1.0 (8aa6a65 / main)
PostgreSQLPostgreSQL 18.4 (Ubuntu 18.4-1.pgdg26.04+1) on x86_64-pc-linux-gnu, compiled by gcc (Ubuntu 15.2.0-16ubuntu1) 15.2.0, 64-bit
meerkat0.1.0 (4a39b1c)
pg_prewarm1.2
vector0.8.4

Search

k10
runs3
warmup500
num_queries10000
S3 archives3://rekall-bench/runs/cohere-100m/2026-07-07/r8i.24xlarge-091552/

Index builds

IndexTypeBuild timeSizeWorkers
hnsw-m24-bqpgvector-hnsw8416.0s43.5 GB32
hnsw-m24-halfvecpgvector-hnsw22012.2s179.2 GB32
mkt-n400000-cctrue-fs16-soar-cfsmeerkat37916.6s20.9 GB32
Index parameters
hnsw-m24-bq: {"ef_construction":200,"encoding":"bit","m":24}
hnsw-m24-halfvec: {"ef_construction":200,"encoding":"halfvec","m":24}
mkt-n400000-cctrue-fs16-soar-cfs: {"boundary_epsilon":0.05,"centroid_compression":true,"centroid_fastscan":true,"fan_out":null,"fastscan":true,"fastscan_bits":null,"nlist":400000,"rerank_vectors":null,"soar_lambda":1.0}
PostgreSQL settings
effective_cache_size = 576 GB
effective_io_concurrency = 256
huge_pages = try
maintenance_work_mem = 307 GB
max_connections = 100
max_parallel_maintenance_workers = 32
max_parallel_workers = 96
random_page_cost = 1.1
shared_buffers = 192 GB
wal_level = replica
work_mem = 1 GB