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Maximem Synapvs Mem0, Zep, Letta, Supermemory, Cognee & Evermind

Agentic context management systems compared on verified LongMemEval benchmarks, retrieval latency, memory capabilities, scope isolation, and developer experience. Synap scored 90.2% on the open-source LongMemEval harness at 15ms P50 latency.

Strong Partial / Limited No / Weak Not verified / Not published

Benchmark note: LongMemEval scores labeled "verified" were measured on Synap's standardized harness (same hardware, same prompts, same conversations, same scoring). The eval harness is open-source. Self-reported vendor scores may differ due to different configurations, hardware, or evaluation subsets.

Benchmark Performance

Feature
Maximem Synap
Mem0
Zep
Letta
Supermemory
Cognee
Evermind
LongMemEval (independently verified)
Best 90.2%
No 57.5%
Not applicable Not verified
Not applicable Not verified
Partial 71.3%
Not applicable Not verified
Not applicable Not verified
LongMemEval (self-reported)
Best 90.2%
Partial 93.4%
Partial 63.8%
Not applicable Not published
Partial 85.4%
Not applicable Not published
Partial 83.0%
P50 retrieval latency
Best 15ms
No 180ms
Not applicable Not published
Not applicable Not published
No 220ms
Not applicable Not published
Not applicable Not published
Open-source eval harness
Best Full config published
No No
No No
No No
No No
No No
No No

Memory Capabilities

Feature
Maximem Synap
Mem0
Zep
Letta
Supermemory
Cognee
Evermind
Memory types
Best 5 structured: facts, preferences, episodes, emotions, temporal
Partial Generic memories with metadata
Partial Entities + relationships + episodes
Partial Generic blocks in 3 tiers
Partial Facts + user profiles
Partial Entities + relationships + summaries
Best MemCells + MemScenes + skills + profiles
Context compaction
Best 4 strategies + quality validation score + preserved facts count
Partial Compression, no quality validation
Partial Graph-based, no validation score
Partial Agent-directed archival
Partial Automatic, no validation score
Partial Graph summarization via memify
Partial MemCell → MemScene consolidation
Contradiction handling
Best Explicit detection & resolution (HITL when needed)
Partial Newer overrides older
Best Old facts invalidated, not deleted
Partial Agent self-edits
Best Explicit detection and resolution
Partial Edge reweighting via memify
Partial Semantic consolidation
Temporal awareness
Best Full bitemporal awareness
Partial Basic timestamps
Best Full bitemporal model
Partial Timestamps on operations
Partial Handles temporal changes
Partial Timestamps on graph edges
Partial Temporal context in MemCells
Entity resolution
Best Automatic, multi-strategy
Partial Pro tier only (graph)
Best Automatic with temporal tracking
No No built-in
Partial Fact extraction with entity tracking
Best LLM-based, graph triplets
Partial Extraction during MemCell formation

Scope & Isolation

Feature
Maximem Synap
Mem0
Zep
Letta
Supermemory
Cognee
Evermind
Memory scoping mechanism
Best Intelligent & automated
No Manual
Partial Semi-automated
No Manual (agent tool calls)
No Manual
Partial Semi-automated
Partial Semi-automated
Scoping levels
Best 4-level: User → Customer → Client → World
Partial 3: user, session, agent
Partial User + group
Partial Per-agent (core + archival)
Partial User-level
Partial Per-user, per-group, shared graphs
Partial User + group + agent
Organizational memory
Best Customer + Client scopes, user stays private
Partial Agent-scope workarounds
Partial Group-level available
No Per-agent only
No User-scoped only
Partial Group and public graphs
Partial Group memory available
Context sharing in agent-swarm systems
Best Native: shared context + agent-specific memories
Partial Shared via scoped memories
Partial Multiple agents query same graph
Best Native coordinator + sub-agents
No Single-agent focused
Partial Multiple agents query same graph
Partial Shared memory layer

Core Architecture

Feature
Maximem Synap
Mem0
Zep
Letta
Supermemory
Cognee
Evermind
Context management paradigm
Best Active: captures, compacts, recalls per agent
No Passive: explicit API calls
Partial Semi-active: auto-extracts, explicit retrieval
Partial Agent-managed: LLM manages tiers
Partial Semi-active: auto-extracts facts
Partial Semi-active: auto-extraction, explicit retrieval
Partial Semi-active: auto-consolidation
Ingestion approach
Best Extract-first: multi-stage pipeline before storage
No Store-first, extract at Pro only
Best Extract-first: temporal graph built
No Agent-directed via tool calls
Partial Extract-then-store: fact extraction
Best 6-stage pipeline
Best Extract-first: MemCells → consolidation
Pipeline customization per agent
Best Custom architecture per agent via YAML config
No Universal pipeline
No Universal graph pipeline
Partial Agents self-edit, universal pipeline
No Universal pipeline
Partial Configurable per dataset, not per-agent
Partial Custom identity templates
Data connectors
Best Connectors for structured data sources
No Text ingestion only
No Text ingestion only
No Text ingestion only
No Text ingestion only
Partial Multiple DB backends supported
Best PDFs, images, URLs

Developer Experience

Feature
Maximem Synap
Mem0
Zep
Letta
Supermemory
Cognee
Evermind
SDK languages
Best Python + JavaScript
Best Python + JavaScript
Partial Python (Graphiti)
Best Python + TypeScript
Best TypeScript + Python
Partial Python
Partial Python
Framework integrations
Best 10 frameworks
Best 8+ frameworks
Partial 4+ frameworks
Partial Own platform
Best 7+ frameworks
Partial 3+ frameworks
Partial API/MCP interface
Async-first SDK
Best Non-blocking, returns immediately
Partial Sync by default
Partial Async episode processing
Partial Server-based async
Partial Sync by default
Partial Async available
Partial Async available
Observability
Best Dashboard: pipelines, memories, entity queue
Partial Analytics at Pro tier
Partial Graph explorer
Best White-box: full prompt + memory transparency
Partial Dashboard available
Best Graph explorer + notebooks
Partial Dashboard available

Last updated: April 2026. Benchmarks sourced from Synap's open-source LongMemEval harness, third-party evaluations, and vendor documentation. Feature availability may change.

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Frequently Asked Questions

On the LongMemEval benchmark, Maximem Synap scored 90.2% on its open-source standardized harness, versus 57.5% for Mem0 and 71.3% for Supermemory on the same harness. Synap also delivers 15ms P50 retrieval latency, native integrations with 10 agent frameworks, and a 4-level scope chain (User → Customer → Client → World) for multi-tenant SaaS deployments. For agentic workloads that need high-accuracy, low-latency context management, Synap is the strongest option in this comparison.

These six projects represent the major architectural approaches in agentic context management today: Mem0 (the most widely adopted agent memory library), Zep (temporal knowledge graph via Graphiti), Letta (OS-inspired tiered memory with agent self-management), Supermemory (combined RAG + memory), Cognee (knowledge-graph-first with 14 retrieval modes), and Evermind/EverOS (self-evolving memory with multimodal ingestion). Comparing against all six gives a complete picture of the trade-offs in this space.

Scores labeled "independently verified" were measured on Synap's open-source LongMemEval harness with identical hardware, prompts, conversations, and scoring. Self-reported numbers come from vendors running their own evaluations on their own configurations and may differ materially from standardized harness results. Zep's 63.8% was reported by a third party and has not been reproduced on Synap's harness yet.

Pick Mem0 for the largest community and simplest memory API. Pick Zep for a mature bitemporal knowledge graph with VPC deployment. Pick Letta for fully open-source self-hosting with white-box memory transparency. Pick Supermemory for SOC 2 / HIPAA compliance certifications today. Pick Cognee for graph-native retrieval with 14 traversal modes. Pick Evermind for self-evolving skills that learn standard operating procedures over time. Each has a real strength that matters for specific use cases.

Agentic context management is the system that captures, structures, compacts, and recalls context for AI agents across conversations and sessions. It goes beyond storing embeddings: it handles entity resolution, temporal awareness, contradiction detection, scope isolation, and per-agent pipeline customization. Synap is an active context management layer — the system manages context so the agent does not have to.

Yes. Synap's core SDK and the LongMemEval evaluation harness are open source. You can self-host the stack or use the managed platform at synap.maximem.ai with a free tier (no credit card).