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Atlaso beats mem0 by +6.6 percentage points on LongMemEval-S under a fully matched protocol — the same Qwen 3.5-9B reader answers for both systems, on the same 500 questions, scored by three independent judges with label-blind normalization (p ≈ 0.007; no judge flips the direction). Most memory-benchmark numbers come from single-vendor pipelines — each system scored against its own reader and its own judge, so the numbers don't compare. We held everything fixed except the memory system.
Benchmark run May 2026 · Corrected & updated August 2026
The multi-judge structure is the point. One judge can favor a system's answer style; independent prompts give a sensitivity band instead of a single number. Reader-matched — the same Qwen 3.5-9B answers for both systems — Atlaso leads in every band, and the strict-judge gap is significant at p ≈ 0.007.
| Judge | Atlaso | mem0 | Δ |
|---|---|---|---|
| Haiku 4.5 strict · accuracy | 53.6% | 47.0% | +6.6pp |
| Haiku 4.5 strict · calibrated F1 | 67.5 | 60.7 | +6.8 |
| GPT-4o strict · calibrated F1 | 69.7 | 63.4 | +6.3 |
| GPT-5 permissive · calibrated F1 | 67.7 | 60.3 | +7.4 |
LongMemEval-S · n = 500 · identical question IDs across arms · matched reader: Qwen 3.5-9B answers for both systems · three independent judges (Anthropic Haiku 4.5 strict, OpenAI GPT-4o strict, OpenAI GPT-5 permissive); F1 shown ×100. Answers are label-blind normalized so a judge can't tell which system produced them. Under the same protocol Letta ties Atlaso exactly — the full study reports the wider field, including that tie.
Memory benchmarks are dominated by single-vendor pipelines: each system is scored end-to-end against its own generator, its own reader, and its own judge. Line two of those numbers up in a deck and the comparison can be off by fifty points purely because the two were generated under different rules.
mem0 publishes a headline 93.4% on LongMemEval-S. Running mem0's default OSS pipeline on the same 500 questions, scored with mem0's ownverbatim judge prompt, we observe 44.2% — a 49.2pp gap under mem0's own rule. We did not reproduce mem0's full managed pipeline, so the honest reading is “methodology + pipeline,” not methodology alone. What is certain: under a fully reader-matched protocol, Atlaso leads mem0 on the same fixture by +6.6 points (p ≈ 0.007).
mem0 published — own pipeline, own judge
mem0 default — matched conditions, mem0's own judge
Atlaso (GPT-5 reader config) — same infra, mem0's own judge
The honest comparison floor sits somewhere between mem0's 44.2% and their published 93.4%; work that reproduces mem0's full managed-platform pipeline will narrow that band. We publish the whole reasoning in the study.
LoCoMo adversarial subset · n = 200 · Haiku 4.5 strict
mem0-default
Atlaso (−11.5pp)
On LoCoMo's temporal-reasoning and planted-distractor questions Atlaso loses to mem0 by 11.5 points. The substrate is currently tuned for questions whose answer either clearly exists in the field or does not; against adversarial distractors it over-abstains. We report the loss because where a system fails is more diagnostic than where it succeeds.
mem0's default configuration runs a gpt-4o-miniextraction call on ingestion — an LLM summarizes each turn before it's stored. Atlaso writes its deposits with zero LLM callsat ingestion. That is a genuine architectural difference, not a scoreboard claim: it changes ingestion cost and behavior, and it's worth knowing which one you're buying.
Read the full study — methodology, run logs, and the limits we publish
They solve related problems at different layers, so the right pick depends on what you're building.
mem0
An open-source memory SDK
mem0 is a library you wire into your own application — you own the storage, the extraction configuration, and the retrieval calls. If you're building a product and want memory as a component you control end-to-end, that's the shape it fits.
Atlaso
A hosted memory layer for the tools you already use
Atlaso connects to the AI tools you already work in and captures and recalls memory automatically — no app to build, nothing to wire up. It works across:
Free for one device and one tool with unlimited memories; Pro is $10/month for unlimited tools and devices sharing one memory.
On LongMemEval-S, Atlaso beats mem0 by 6.6 points under a fully matched reader and strict judge (p≈0.007), and by 6–7 F1 points across three independent judges — no judge flips the direction. On the LoCoMo benchmark, mem0 leads Atlaso by 11.5 points. Atlaso publishes both results, because one benchmark never tells the whole story.
The study holds everything fixed except the memory system: identical question IDs, the same Qwen 3.5-9B reader answering for both systems, and three independent judges scoring label-blind normalized answers. An earlier version compared mismatched readers; Atlaso found the error in its own artifacts, corrected the page, and published the correction.
Atlaso is a mem0 alternative if you want memory for the AI tools you already use: mem0 is primarily an API developers build into their own apps, while Atlaso installs in minutes and gives Claude Code, Cursor, Codex, and more one shared memory — no code required.
mem0 leads Atlaso by 11.5 points on the LoCoMo benchmark, has a larger open-source community, and its self-hosted option gives developers more infrastructure control. Atlaso publishes this openly — the reader-matched LongMemEval-S win matters more for daily coding-tool memory, but no system wins everywhere.
Yes. Atlaso Build, at $25 a month, gives your own app or hardware a hosted memory API — a private, isolated memory per end-user, project API keys for server-to-server use, and no per-call charges. The consumer product and the API share the same memory engine.
Yes — they solve different problems. mem0 typically lives inside a product you're building, giving that app's users memory. Atlaso gives you one shared memory across the AI tools you personally use. A developer can build on mem0 or Atlaso Build while using Atlaso for their own tools.
Connect Atlaso to the tools you already use and stop starting from zero. Free to start — no credit card required.