Agent-S vs GenericAgent
The two are close in size: 12.2k stars for Agent-S, 14.1k for GenericAgent. Over the days we have tracked them Agent-S moved +3.9% and GenericAgent +11.8%, so GenericAgent is growing faster right now.
GenericAgent leads on context depth and setup ease. Agent-S 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
An open-source, research-backed GUI agent framework that combines grounding models and optional local code execution and achieves SOTA (surpassing human performance on OSWorld).
- Stars
- 12.2k
- Tracked growth
- +3.9%
- Maturity
- ●●●●●
- Last commit
- 35d ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Your API keys (provider-dependent)
Self-evolving agent that crystallizes each solved task into a persistent, reusable personal skill tree from a minimal (~3K-line) seed.
- Stars
- 14.1k
- Tracked growth
- +11.8%
- Maturity
- ●●●●●
- Last commit
- 2d ago
- Language
- Python
- License
- MIT
- Cost to run
- Your LLM API key; provider charges apply
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 | Agent-S | GenericAgent |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Single-screen context | ●●●●● Whole-repo analysis |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Basic filters | ●●●●● Human-in-the-loop |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Configurable params | ●●●●● Config & prompts |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Cloud APIs (your key) | ●●●●● Cloud API key |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Bring-your-own key | ●●●●● Bring-your-own-key |
Setup ease What it takes to get a first useful run out of it. | ●●●●● Config + API key | ●●●●● One-line installer |
Which one to pick
Pick Agent-S if…
SOTA performance — pick Agent S when you need a research-grade, open-source GUI agent with grounding-model support and optional local code execution.
Pick GenericAgent if…
Self-evolving — pick this when you want an agent that autonomously builds reusable skills and gains system-level desktop/browser control over time.
- Context depth: Whole-repo analysis (5/5 against 1/5)
- Setup ease: One-line installer (5/5 against 3/5)
What people want from each one
simular-ai/Agent-S
Hacker News: Show HN: Agent S: an open agentic framework that uses computers drew 2 points and 1 comments.
lsdefine/GenericAgent
Questions people ask
Is Agent-S better than GenericAgent?
GenericAgent leads on context depth and setup ease. Agent-S does not take any axis by a clear margin. Agent-S is worth picking when sOTA performance — pick Agent S when you need a research-grade, open-source GUI agent with grounding-model support and optional local code execution.
Which of Agent-S and GenericAgent keeps my code private?
Agent-S: Cloud APIs (your key) (3/5). GenericAgent: Cloud API key (3/5).
What does each one cost to run?
Agent-S: Your API keys (provider-dependent). GenericAgent: Your LLM API key; provider charges apply.
Full profiles: simular-ai/Agent-S and lsdefine/GenericAgent. Everything else in Computer use.