Benchmarks

Benchmark retrieval quality from the public CLI against local fixtures before changing models, modes, or defaults. GNO's research loops are built around measurable wins, not vibes.

Install GNO Read the docs

Use cases: Evaluating a new embedding or reranker before shipping; Comparing candidates against a stable baseline; Catching retrieval regressions with a fixture your team owns

What it gives you

Public `gno bench <fixture>` command for repeatable checks
BM25, vector, and hybrid mode comparisons from the same fixture
Recall@K, precision, nDCG, MRR, and latency metrics
Per-query misses and hit lists for debugging regressions
JSON output for CI, model experiments, and release notes
Example fixture schema for team-owned benchmark corpora

Try it yourself

Representative commands and entry points. Full reference lives in the documentation.

gno bench docs/examples/bench-fixture.json

gno bench fixture.json --modes bm25,hybrid

gno bench fixture.json --json

Keep reading

Related features and docs.

Fine-tuned models

/features/fine-tuned-models

Open

Hybrid search

/features/hybrid-search

Open

How search works

/docs/how-search-works

Open

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