OMEM vs Mem0 vs Zep: which agent memory answers your question?
These three tools get compared because they all say “memory for AI agents,” but they are built for different questions. This page is the comparison we would want to read: specific, dated, and honest about where each one wins, including where we lose. Last checked: September 2026.
The short version
Mem0 is the most widely adopted: you hand it conversations, an LLM distills them into memories and decides how new facts update old ones, and recall quality with near-zero integration work is the product. Zep builds a temporal knowledge graph: an LLM extracts entities and facts, and conflicting facts are invalidated with validity intervals instead of deleted, which gives real temporal provenance. OMEM is an accountability layer: no model decides what is stored or what is true, contradictions stay on the record with both sides, a named human approves risky actions, and the engine that reads the record must replay it byte-identically, verified in CI on every commit.
The structural difference underneath every row of the table: Mem0 and Zep put an LLM in the write path, because their job is to manage memory for you. OMEM refuses to, because its job is to be evidence. Both designs are correct for their question.
Side by side
| Mem0 | Zep | OMEM | |
|---|---|---|---|
| What it optimizes | Recall quality with minimal integration work | Temporal knowledge graph over your data | A defensible record of belief and action |
| On conflicting facts | An LLM decides how the new fact updates the old | An LLM invalidates edges, with validity intervals | Both sides kept; a contradiction must be declared, never inferred |
| LLM in the write path | Yes, it distills and updates memories | Yes, it extracts entities and facts | No. Nothing stored is model-decided |
| History of a belief | Memory history is available | Validity intervals on graph edges | Append-only log; ask what was believed at any past moment |
| Why-provenance | Similarity and source metadata | Graph paths with time bounds | Evidence chain per belief: source, time, basis, what it contradicted |
| Action gating | Not its job | Not its job | Named-approver gate; refusals recorded with reasons |
| Tamper evidence | Standard database guarantees | Standard database guarantees | Frozen engine, byte-identical replay verified in CI on every commit |
| Network posture | Hosted service, or self-host the OSS core | Hosted cloud; the Graphiti engine is OSS | Self-hosted only; a CI test fails the build on any non-loopback connection |
| Erasure | Delete APIs | Delete APIs | Right-to-be-forgotten with replay-verified erasure |
| Adoption and ecosystem | The widest: default memory in AWS's Agent SDK, many framework integrations | Established, funded, latency-focused | Early. Small community, one maintainer, integrations growing |
| License and cost | OSS core plus paid hosted tiers | OSS engine plus paid cloud | MIT, free, self-hosted; the paid offering is hands-on pilot time |
Descriptions of Mem0 and Zep come from their public documentation as of September 2026; if something is out of date, open an issue and it gets fixed.
Where Mem0 and Zep genuinely win
If you want memory that manages itself from raw conversation, both beat OMEM today. OMEM makes you assert claims explicitly, subjects and proposition, which is more integration work; that explicitness is where its guarantees come from, but it is honest to call it a cost. Mem0’s ecosystem is far larger, and if you want a hosted service with an SLA, OMEM does not offer one: it is self-hosted by design. Zep’s graph gives you entity-level queries OMEM does not attempt. If your agent is a chatbot whose worst failure is a wrong preference, their trade is the right one.
Where OMEM wins
The stakes change when an agent acts on someone’s behalf and a client, an auditor, or a regulator can ask “why did it do that?” An LLM-curated memory cannot fully answer, because the curation itself is an unrecorded judgment: the model that decided the new fact should replace the old one left no defensible reason behind. OMEM’s answer is structural. Every belief carries its evidence chain. Contradictions keep both sides. Risky actions wait for a named approver, and refusals are recorded with reasons. The engine is frozen: it must replay the whole log byte-identically, checked in CI on every commit, so not even an upgrade can change what was said. And a CI test fails the build if the server ever makes a non-loopback connection, so “nothing leaves your environment” is a test result, not a promise.
We also benchmark this differently, and publish it: Witness measures truthfulness duties, keeping contradictions, refusing unsupported claims, surviving retraction, rather than recall accuracy. It ships adapters for Mem0 and Graphiti so you can run the comparison yourself, with your own keys, rather than trusting our numbers.
Choose honestly
- Choose Mem0 for the best self-managing recall with the least work, the biggest ecosystem, and a hosted option.
- Choose Zep when you want temporal, entity-level structure over your data and graph queries against it.
- Choose OMEM when someone can ask you to prove why the agent believed and did what it did: agents that act for clients, security reviews, EU AI Act Article 12 exposure.
- Or run two. A recall layer behind the model and OMEM in front of the action is a coherent architecture, not a compromise.