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Cohere-100M — 2026-07-16

r8i.8xlarge · peak recall 0.9969 @ 28 QPS
“resized: 100M dataset build on 24xlarge downsized to 8xlarge”

QPS at recall

RecallMeerkatpgvector HNSW (halfvec)Δ vs best competitor
0.90558100+458%
0.9527272+276%
0.9962— (max r=0.986)—

Latency at recall

Meerkatpgvector HNSW (halfvec)Δ vs best competitor
@ recall 0.90
p501.77 ms8.41 ms-79%
p952.26 ms19.28 ms-88%
p992.63 ms24.97 ms-89%
@ recall 0.95
p503.61 ms14.19 ms-75%
p954.48 ms17.51 ms-74%
p995.42 ms19.87 ms-73%
@ recall 0.99
p5015.98 ms——
p9519.15 ms——
p9924.32 ms——

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-defaults · pgvector HNSW (halfvec) @0.90: hnsw-m24-halfvec · Meerkat @0.95: mkt-defaults · pgvector HNSW (halfvec) @0.95: hnsw-m24-halfvec · Meerkat @0.99: mkt-defaults

Build comparison

Meerkatpgvector HNSW (halfvec)Δ vs best competitor
Build time3443 s22212 s-85%
Index size24.9 GB179.2 GB-86%

Build stats are for the configuration backing each column's best operating point: Meerkat = mkt-defaults, prewarmed · pgvector HNSW (halfvec) = hnsw-m24-halfvec, prewarmed.

Plots

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

Host

Instance typer8i.8xlarge
Hostnameip-172-31-75-2
CPUIntel(R) Xeon(R) 6975P-C (32 vCPU)
Memory248 GB
OSUbuntu 26.04 LTS
Kernel7.0.0-1008-aws

Versions

rekall0.1.0 (c1f5545 / 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 (1f3ad94)
pg_prewarm1.2
vector0.8.5

Search

k10
runs3
warmup500
num_queries10000
S3 archives3://rekall-bench/runs/cohere-100m/2026-07-16/r8i.8xlarge-081638/

Index builds

IndexTypeBuild timeSizeWorkers
hnsw-m24-halfvecpgvector-hnsw22212.1s179.2 GB32
mkt-defaultsmeerkat3442.7s24.9 GB32
Index parameters
hnsw-m24-halfvec: {"ef_construction":200,"encoding":"halfvec","m":24}
mkt-defaults: {"boundary_epsilon":null,"centroid_compression":null,"centroid_fastscan":null,"fan_out":null,"fastscan":null,"fastscan_bits":null,"nlist":null,"rerank_vectors":null,"soar_lambda":null}
PostgreSQL settings
effective_cache_size = 192 GB
effective_io_concurrency = 256
huge_pages = try
maintenance_work_mem = 102 GB
max_connections = 100
max_parallel_maintenance_workers = 16
max_parallel_workers = 32
random_page_cost = 1.1
shared_buffers = 64 GB
wal_level = replica
work_mem = 1 GB