Agentlas hits 96.4% on LongMemEval without calling a model for retrieval
minglingj · reddit · 2026-07-25
A new project called Agentlas claims 96.4% accuracy on LongMemEval without calling an LLM during retrieval, and 91.5% on LoCoMo.
Its memory design stays local in a single SQLite file rather than a separate memory server. The system splits memory into four ownership zones: user identity, project context, individual agent learning records, and team-shared facts. Instead of asking an LLM every time, it combines a lightweight on-device embedding model with keyword search to filter irrelevant results and reduce hallucinations. The latest update also adds independent per-member identifiers, plus a self-evolving mechanism that can propose improvements after repeated failures and let users approve or rollback them with one click.
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