AI-Scientist-v2 vs Auto-claude-code-research-in-sleep
Auto-claude-code-research-in-sleep is much bigger: 17.8k stars against 7.4k. Over the days we have tracked them AI-Scientist-v2 moved +6.8% and Auto-claude-code-research-in-sleep +29.2%, so Auto-claude-code-research-in-sleep is growing faster right now.
Auto-claude-code-research-in-sleep leads on noise control and customization. AI-Scientist-v2 does not take any axis by a clear margin.
Stars and commit dates come from our own daily tracking. The six axes are read off each project's documentation by our review pipeline, so they describe what a project says about itself, not what we measured in its code.
Where they stand today
End-to-end autonomous scientific discovery: it uses progressive agentic tree search to ideate, run experiments, analyze results, and draft papers without human-authored templates.
- Stars
- 7.4k
- Tracked growth
- +6.8%
- Maturity
- ●●●●●
- Last commit
- 306d ago
- Language
- Python
- License
- NOASSERTION
- Cost to run
- Your API key, per-run (README cites ≈$15–$20 for experiments + ≈$5 for writing with default models)
Provides a lightweight, skill-based autonomous research workflow with built-in cross-model reviewer loops and deterministic integrity audits (Anti-Autoresearch), targeted at reproducible ML research rather than generic agent tasks.
- Stars
- 17.8k
- Tracked growth
- +29.2%
- Maturity
- ●●●●●
- Last commit
- 4h ago
- Language
- Python
- License
- MIT
- Cost to run
- Your API key or model subscription
Six axes, head to head
Each axis runs 0 to 5. The label under a score is what that project's own docs claim, not a category average.
| Axis | AI-Scientist-v2 | Auto-claude-code-research-in-sleep |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Related files | ●●●●● Diff + related files |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Config-based controls | ●●●●● Severity gating & audits |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Configurable params | ●●●●● Skill & per-call config |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Cloud APIs (your keys) | ●●●●● Cloud APIs (your key) |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Multiple providers | ●●●●● Several providers |
Setup ease What it takes to get a first useful run out of it. | ●●●●● GPU install required | ●●●●● Config + API key |
Which one to pick
Pick AI-Scientist-v2 if…
End-to-end autonomy — pick this when you want a research pipeline that generates hypotheses, executes experiments, and produces writeups using configurable agentic tree search across multiple LLM providers.
Pick Auto-claude-code-research-in-sleep if…
Research-focused — pick ARIS when you need an audited, multi-model research automation stack with reviewer gating, integrity checks, and per-skill customization.
- Noise control: Severity gating & audits (5/5 against 3/5)
- Customization: Skill & per-call config (5/5 against 3/5)
What people want from each one
SakanaAI/AI-Scientist-v2
wanshuiyin/Auto-claude-code-research-in-sleep
Questions people ask
Is AI-Scientist-v2 better than Auto-claude-code-research-in-sleep?
Auto-claude-code-research-in-sleep leads on noise control and customization. AI-Scientist-v2 does not take any axis by a clear margin. AI-Scientist-v2 is worth picking when end-to-end autonomy — pick this when you want a research pipeline that generates hypotheses, executes experiments, and produces writeups using configurable agentic tree search across multiple LLM providers.
Which of AI-Scientist-v2 and Auto-claude-code-research-in-sleep keeps my code private?
AI-Scientist-v2: Cloud APIs (your keys) (3/5). Auto-claude-code-research-in-sleep: Cloud APIs (your key) (3/5).
What does each one cost to run?
AI-Scientist-v2: Your API key, per-run (README cites ≈$15–$20 for experiments + ≈$5 for writing with default models). Auto-claude-code-research-in-sleep: Your API key or model subscription.
Full profiles: SakanaAI/AI-Scientist-v2 and wanshuiyin/Auto-claude-code-research-in-sleep. Everything else in ML experiment agents.