benchmarks · reproducible · offline
Honest benchmarks
The AI-memory market publishes leaderboard numbers that don't survive independent reproduction. We do it differently: every Mnem figure on this page comes from an open harness you can run yourself — offline, in one command.
Our rules
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Mnem, measured open harness
| Category | Items | Recall@1 | Recall@5 |
|---|---|---|---|
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Reproduce it: python benchmarks/run_benchmarks.py — dataset, scorer, and config ship with the app's benchmark kit. No network access required.
What competitors claim vs. what reproductions found
These are not our measurements. Claims are the vendors' own self-reported figures; reproductions are third-party runs (some by competing vendors — noted where known). We list both because, as of 2026, cross-vendor leaderboard numbers are harness-relative and not comparable.
The columns that decide product fit
| Where memories live | Recall path | Portability |
|---|
Competitor claims and reproductions cited as of the date in each entry. Nothing on this page is hand-edited: figures are generated from harness output.
Run the numbers yourself.
Sub-10ms recall on your machine, with nothing leaving it.