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Supermemory

by Supermemory

System Card

OrganizationSupermemory
Released2024-06
Architecturegraph-rag / Vector graph engine with ontology-aware edges
DetailsCustom vector graph engine that tracks relationships between memories instead of similarity scores. Five-layer context stack: connectors, extractors, retrieval, memory graph, and user profiles. Handles contradictions, temporal changes, and knowledge updates without corrupting existing state. Sub-300ms recall speed. Shipped with MCP plugin for cross-LLM memory portability across ChatGPT, Claude, and Gemini.
Parameters—
Domainagent-memorypersonalizationepisodic-sessionknowledge-graph
Open SourcePartial
PaperView Paper
WebsiteVisit
CodeRepository
vector-graphmcpcross-llmsub-300msknowledge-updatestemporal-reasoningagent-memoryyc-backed

Capability Profile

Benchmark Scores

6 of 14 benchmarks
Data Transparency:1 self-reported5 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
83.594pEstimated
MemoryBank
81.284pEstimated
Cross-Session Memory
1/1
LongMemEval
81.688pSelf-Reported
Multi-Hop QA
2/3
BABILong
no data
MultiHop-RAG
72.454pEstimated
HotpotQA
78.693pEstimated
Agent Task Memory
1/1
AgentBench-Mem
68.518pEstimated
Personalization
0/1
PerLTQA
no data
Factuality / Grounding
0/1
RAGAS
no data
Sources:supermemory.ai/research — 81.6% overall accuracy (GPT-4o configuration)Arena estimate — no published LoCoMo score from SupermemoryArena estimate — derived from capability profile, not independently verified