nanoclaw vs DSHA
nanoclaw is much bigger: 31.0k stars against 2.0k. Over the days we have tracked them nanoclaw moved +2.1% and DSHA +701.6%, so DSHA is growing faster right now.
nanoclaw leads on context depth and model freedom. DSHA 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
Provides compact, auditable agent runtime with true OS-level container isolation so agents run in separate containers with explicit mounts instead of one large shared process.
- Stars
- 31.0k
- Tracked growth
- +2.1%
- Maturity
- ●●●●●
- Last commit
- 2h ago
- Language
- TypeScript
- License
- MIT
- Cost to run
- Your API key (Anthropic/OpenAI) or local models
Runs DeepSeek Harness on unrooted Android with an integrated proroot container runtime, ADB direct device channel and real-time floating AI output overlay.
- Stars
- 2.0k
- Tracked growth
- +701.6%
- Maturity
- ●●●●●
- Last commit
- 5h ago
- Language
- Java
- License
- MIT
- Cost to run
- Your DeepSeek API key
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 | nanoclaw | DSHA |
|---|---|---|
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 access | ●●●●● Diff only |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Basic gating | ●●●●● Confirmations & prechecks |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Code-based customization | ●●●●● Configurable settings |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Self-hostable | ●●●●● Self-hostable |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● Bring-your-own key | ●●●●● API key supported |
Setup ease What it takes to get a first useful run out of it. | ●●●●● One-script install | ●●●●● One-click install |
Which one to pick
Pick nanoclaw if…
Privacy-first — run agents in isolated Docker containers on your own machine with per-agent mounts and the option to use local or BYO models.
- Context depth: Related files access (3/5 against 1/5)
- Model freedom: Bring-your-own key (5/5 against 3/5)
Pick DSHA if…
Mobile-first — run DeepSeek on unrooted Android with one-click install, proroot performance gains, persistent local data and direct ADB device integration.
What people want from each one
nanocoai/nanoclaw
Hacker News: Show HN: NanoClaw – “Clawdbot” in 500 lines of TS with Apple container isolation drew 533 points and 224 comments.
Questions people ask
Is nanoclaw better than DSHA?
nanoclaw leads on context depth and model freedom. DSHA does not take any axis by a clear margin. nanoclaw is worth picking when privacy-first — run agents in isolated Docker containers on your own machine with per-agent mounts and the option to use local or BYO models.
Which of nanoclaw and DSHA keeps my code private?
nanoclaw: Self-hostable (4/5). DSHA: Self-hostable (4/5).
What does each one cost to run?
nanoclaw: Your API key (Anthropic/OpenAI) or local models. DSHA: Your DeepSeek API key.
Full profiles: nanocoai/nanoclaw and qiannianhuanxiang/DSHA. Everything else in Runtimes & sandboxes.