AI-Scientist vs EvoScientist
AI-Scientist is much bigger: 14.5k stars against 4.6k. Over the days we have tracked them AI-Scientist moved +1.6% and EvoScientist +7.2%, so EvoScientist is growing faster right now.
They split the axes: AI-Scientist leads on model freedom, EvoScientist on customization.
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
Automates end-to-end scientific discovery by generating hypotheses, running experiments, and producing full LaTeX papers from templates.
- Stars
- 14.5k
- Tracked growth
- +1.6%
- Maturity
- ●●●●●
- Last commit
- 260d ago
- Language
- Jupyter Notebook
- License
- NOASSERTION
- Cost to run
- Requires your API keys for cloud models; local GPU needed for open-weight runs.
Auto-distills a growing memory/knowledge graph into reusable AutoSkills and a multi-agent research loop, enabling long-running self-evolving AI scientists.
- Stars
- 4.6k
- Tracked growth
- +7.2%
- Maturity
- ●●●●●
- Last commit
- 3h ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Requires your cloud model API keys (per-use billing)
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 | EvoScientist |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Template-level view | ●●●●● Diff + related files |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Ensemble reviews | ●●●●● Basic filtering & gating |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Template + prompt config | ●●●●● Extensible skills & config |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Self-hostable (local GPU) | ●●●●● Self-hostable |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● BYOK + local models | ●●●●● Multiple cloud providers |
Setup ease What it takes to get a first useful run out of it. | ●●●●● GPU + dependencies | ●●●●● Config + API key |
Which one to pick
Pick AI-Scientist if…
End-to-end experiment automation — pick this when you want a research-focused system that generates ideas, runs experiments on local GPUs, and compiles full papers automatically.
- Model freedom: BYOK + local models (5/5 against 3/5)
Pick EvoScientist if…
Self-evolving research — pick EvoScientist when you want an opinionated, multi-agent system that autonomously builds a persistent knowledge graph and drafts reusable skills for iterative scientific workflows.
- Customization: Extensible skills & config (5/5 against 3/5)
What people want from each one
SakanaAI/AI-Scientist
EvoScientist/EvoScientist
Questions people ask
Is AI-Scientist better than EvoScientist?
They split the axes: AI-Scientist leads on model freedom, EvoScientist on customization. AI-Scientist is worth picking when end-to-end experiment automation — pick this when you want a research-focused system that generates ideas, runs experiments on local GPUs, and compiles full papers automatically.
Which of AI-Scientist and EvoScientist keeps my code private?
AI-Scientist: Self-hostable (local GPU) (4/5). EvoScientist: Self-hostable (4/5).
What does each one cost to run?
AI-Scientist: Requires your API keys for cloud models; local GPU needed for open-weight runs.. EvoScientist: Requires your cloud model API keys (per-use billing).
Full profiles: SakanaAI/AI-Scientist and EvoScientist/EvoScientist. Everything else in ML experiment agents.