MIND LAYEREvolving character projectTested capabilitiesConfigurationREST APIBenchmarksData lifecycle and architecture

Benchmarks

These are measured diagnostics for this standalone edition. They are not scores for the full hosted platform and do not establish general memory quality.

Retrieval quality: synthetic-v1

The unchanged authored dataset contains 12 synthetic facts and 12 queries, including exact terms, inflection, paraphrases and one two-evidence query. Both runs use k=3. No real users or customer data are included. The query labels are used only for scoring, not ingestion or retrieval.

Retrieval mode Mean recall@3 MRR@3 Provider
Most recently inserted 3 facts baseline 25.00% Not measured None
BM25 lexical 75.00% 0.7500 None
Hybrid BM25 + embeddings 100.00% 0.9583 gemini-embedding-001

Recall@3 is the fraction of required evidence memories retrieved, averaged over queries. MRR@3 is the reciprocal rank of the first relevant memory, or zero if none is retrieved. A high score on this tiny authored set is not a statistically reliable quality estimate. Lexical search misses several paraphrases; hybrid retrieval recovers them in this run. There is no answer-generation judge here.

Dataset SHA-256: 297811d32167a59cfb1fe7bd1bfcdc03633c5b8cc1606e13dfff1d810fcd489d. Lexical measured: 2026-09-10T19:56:11Z. Hybrid measured: 2026-09-10T19:57:06Z. Environment: darwin/arm64, 14 logical CPUs, go1.26.0. Models and machines can change results.

Local latency

The separate scale test contains 1,000 authored synthetic records, with 30 sequential warmed-up keyword queries in one process. It includes database reads and retrieval, without HTTP or provider calls.

Measurement Result
p50 query latency 3.267 ms
p95 query latency 4.380 ms
1,000 individual durable writes 9.275 seconds

This is not cold-start latency, concurrent throughput, a vector-index scaling test, or a provider-latency claim. Multilingual tokenizers load models lazily. Semantic search scans the selected scope's vectors; it is not an ANN service.

Reproduce

go run ./cmd/benchmark
# Requires configured provider environment and incurs provider usage:
go run ./cmd/benchmark -mode hybrid -live -iterations 0
# Optional separate provider smoke test (synthetic data only):
MIND_LAYER_LIVE_TEST=1 go test -run '^TestLiveProvider$' -count=1 -v .

Raw per-query results live in benchmarks/results/lexical.json and benchmarks/results/hybrid.json. The fixture is benchmarks/synthetic.json. The live smoke report is benchmarks/results/live-smoke.json; it records one passed Gemini extraction/retrieval/answer test, not a quality leaderboard score. No token-price estimates or competitor numbers are invented.

Public benchmarks: not yet measured

Benchmark Why relevant This edition's status
LongMemEval Long-term memory QA, updates, temporal reasoning, multi-session evidence and abstention Not run; no score claimed
LoCoMo Long conversational histories with QA and evidence annotations Not run; no score claimed

For a comparable public result, pin the dataset revision and split, include every evaluation case (including abstention), document ingestion/chunking and retrieval settings, and use the benchmark's official scoring protocol. Report provider models, token usage/cost, timing and all failures. Retrieval recall alone must not be presented as answer accuracy. External datasets and generated transcripts must remain outside the public source tree; do not bundle them as fixtures.