Benchmarks

Five benchmarks, first on three

With one open model writing memory for every system, Reglos leads EverOS, MemOS and Mem0 on PersonaMem-v2, LongMemEval-S and LoCoMo.

Benchmarks

Results

01

Full results

Qwen3.8-27B answering

SystemPersonaMem-v2LongMemEval-SLoCoMoBEAM-100KBEAM-500K
Reglos61.384.087.267.965.6
EverOS53.680.481.569.558.3
MemOS53.873.075.767.062.9
Mem045.065.657.869.466.8

GPT-5.6 Luna answering

SystemPersonaMem-v2LongMemEval-SLoCoMoBEAM-100KBEAM-500K
Reglos57.587.289.565.965.0
EverOS49.680.086.167.557.0
MemOS50.574.078.864.461.3
Mem045.264.462.468.859.9
02

Where it leads

91.4%
Questions involving sensitive information
PersonaMem-v2 · other memory systems 42.9%–47.6%
63.1%
Things the user asked to forget
PersonaMem-v2 · EverOS 42.8%, Mem0 11.8%
98.2%
What the assistant itself said earlier
LongMemEval-S · EverOS 67.9%
+6.5
Gained by four self-improvement steps
54.2% → 60.7% · accepted on held-out users

Accuracy holds as more is written: writing only 25%, 50%, 75% or 100% of each history and asking the same questions, Reglos leads at every step.

All numbers are from our paper Reglos: A Self-Evolving Personal Memory Agent with Recursive Self-Improvement (arXiv:2611.06049)

Reglos

Self-evolving memory infrastructure for personal AI agents.

hello@reglos.ai
Mechanisms
  • Row-level isolationthree-level scope + database RLS
  • Change historywrites, vetoes and deletes, all traceable
  • Redaction firstkeys and card numbers stopped before the model

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