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MemOS

by MemTensor (Li, Zhang, et al.)

System Card

OrganizationMemTensor (Li, Zhang, et al.)
Released2025-05
Architectureagentic-workflow / Memory OS with MemCube units across plaintext/activation/parameter
DetailsTreats memory as a managed system resource. MemCube units encapsulate content plus metadata and can be composed/migrated/fused across plaintext, activation, and parameter memory. Implements permissioning, lifecycle management, and evolvability.
Parameters—
Domainagent-memorylifelong-learning
Open SourceYes
PaperView Paper
CodeRepository
memory-osmemcubesystem-resourcelifecycle

Capability Profile

Benchmark Scores

6 of 14 benchmarks
Data Transparency:2 self-reported4 estimated
Long-Context Retrieval
0/5
RULER
no data
NIAH
no data
LooGLE
no data
LongBench
no data
∞Bench
no data
Multi-Turn Recall
2/2
LoCoMo
75.857pSelf-Reported
MemoryBank
75.349pEstimated
Cross-Session Memory
1/1
LongMemEval
77.863pSelf-Reported
Multi-Hop QA
2/3
BABILong
72.118pEstimated
MultiHop-RAG
no data
HotpotQA
71.852pEstimated
Agent Task Memory
1/1
AgentBench-Mem
7226pEstimated
Personalization
0/1
PerLTQA
no data
Factuality / Grounding
0/1
RAGAS
no data
Sources:arXiv:2507.03724 — MemOS-1031 average, Table 3 — Average across LongMemEval categories; outperforms Memobase 72.4%arXiv:2507.03724 — MemOS-1031 overall LLM Judge Score — Headline LoCoMo LLM-as-Judge score; also shown on MemTensor GitHub READMEArena estimate — derived from capability profile, not independently verified