Atlaso beats mem0 by 6.6 points on LongMemEval-S under a fully matched protocol, and loses to it by 11.5 points on LoCoMo: both results are published here.
Benchmark run May 2026. Corrected and updated August 2026.
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. One judge can favour a system's answer style, so independent prompts give a band instead of a single number. 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 cannot tell which system produced them. Under the same protocol Letta ties Atlaso exactly, and 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 made under different rules. mem0 publishes a headline 93.4% on LongMemEval-S. Running mem0's default open-source pipeline on the same 500 questions, scored with mem0's own verbatim judge prompt, we observe 44.2%, a 49.2pp gap under mem0's own rule.
93.4%
mem0 published, on its own pipeline and its own judge
44.2%
mem0 default, matched conditions, scored with mem0's own judge
56.4%
Atlaso in the GPT-5 reader config, same infrastructure, mem0's own judge
We did not reproduce mem0's full managed pipeline, so the honest reading is methodology plus pipeline, not methodology alone. The honest comparison floor sits somewhere between mem0's 44.2% and their published 93.4%, and work that reproduces mem0's full managed platform will narrow that band. What is certain: under a fully reader-matched protocol, Atlaso leads mem0 on the same fixture by +6.6 points (p ≈ 0.007).
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, and against adversarial distractors it over-abstains. We report the loss because where a system fails is more diagnostic than where it succeeds.
35.5%
mem0 default
24.0%
Atlaso, 11.5 points behind
LoCoMo adversarial subset, n = 200, Haiku 4.5 strict. Read the full study, with the methodology, the run logs, and the limits we publish.
mem0's default configuration runs a gpt-4o-mini extraction call on ingestion, so a model summarizes each turn before it is stored. Atlaso writes its deposits with zero LLM calls at ingestion. That is a genuine architectural difference, not a scoreboard claim: it changes ingestion cost and behaviour, and it is worth knowing which one you are buying.
mem0 is a library you build with, Atlaso is a memory layer you turn on. They solve related problems at different layers, so the right pick depends on what you are building.
mem0 is a library you wire into your own application, so you own the storage, the extraction configuration, and the retrieval calls. If you are building a product and want memory as a component you control end to end, that is the shape it fits.
Atlaso connects to the AI tools you already work in, Claude Code, Cursor, Codex, Claude Desktop, OpenCode and Antigravity, and captures and recalls memory automatically. Free for one device and one tool with unlimited memories; Pro is $10 a 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, with no judge flipping 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.
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