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Mem0g

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

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Corpus findings

2026-04-11 / skill-finderMem0 Memory Compression Engine: 90% Token Reduction with Graph-Enhanced Knowledge Graphs — 26% Accuracy Gain Over OpenAI on LOCOMOMem0's memory compression architecture reduces prompt tokens from ~26K to ~1.8K per conversation (90% reduction) while delivering 26% relative accuracy gains over OpenAI on the LOCOMO benchmark with 91% lower p95 latency. The graph-enhanced variant Mem0g builds a directed labeled knowledge graph alongside the vector store during extraction, with entity extraction, relation generation, and conflict detection preventing contradictory information from corrupting agent memory.
2026-03-23 / skill-finderMem0g Graph Memory: Entity-Relationship Graphs for Production Agent Memory Achieve 26% Accuracy Boost and 91% Lower p95 Latency vs OpenAIMem0's graph memory variant (Mem0g) stores memories as directed labeled graphs where entities are nodes and relationships are edges, with LLM-powered conflict detection/resolution on update. Benchmarks show 26% relative improvement on LLM-as-a-Judge metrics versus OpenAI memory, 91% lower p95 latency, and 90% token savings at inference. The graph structure excels at multi-hop relationship queries that flat vector memory fails on. GA'd January 2026 with native LangChain/LlamaIndex integrations.

Graph relationships

RELEASED
mem0
Mem0 released graph memory variant Mem0g in January 2026.
Source finding
SUPPORTS
LangChain
Mem0g has native LangChain integration.
Source finding
COMPETES WITH
OpenAI
Mem0g outperforms OpenAI memory by 26% on LLM-as-a-Judge evaluation.
Source finding
RELEASED
mem0 -> Mem0g
Mem0 released graph memory variant Mem0g in January 2026.
Source finding

Source trail

Mem0g Mem0 — AI Memory Research

Graph sources

entity graphfindings textkg edgeskg entitiesnewsletter issues

Mem0g intelligence trail | MindPattern