DeepTutor vs nanobot
The two are close in size: 38.8k stars for DeepTutor, 47.7k for nanobot. Over the days we have tracked them DeepTutor moved +58.3% and nanobot +4.3%, so DeepTutor is growing faster right now.
Neither one leads on the six capability axes, so the choice comes down to which of them fits the way you already work.
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
A self-hostable, multi-agent tutoring platform with built-in RAG, three-layer persistent memory and a pluginable Skills ecosystem for lifelong personalized learning.
- Stars
- 38.8k
- Tracked growth
- +58.3%
- Maturity
- ●●●●●
- Last commit
- 2d ago
- Language
- Python
- License
- Apache-2.0
- Cost to run
- Free to self-host; uses your model API key or local LLMs
An ultra-lightweight, self-hosted personal agent runtime that pairs a small, readable core with built-in WebUI, persistent memory, automation, and flexible model routing for long-running workflows.
- Stars
- 47.7k
- Tracked growth
- +4.3%
- Maturity
- ●●●●●
- Last commit
- 18h ago
- Language
- Python
- License
- MIT
- Cost to run
- Your API key; optional paid hosting
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 | DeepTutor | nanobot |
|---|---|---|
Context depth How much of your codebase it sees before it answers: the open diff, the diff plus related files, or the whole repository. | ●●●●● Multi-doc RAG | ●●●●● Diff + related files |
Noise control How it keeps output volume down — severity thresholds, deduplication, incremental runs over new commits only. | ●●●●● Basic filters | ●●●●● Basic filters/config |
Customization How far it bends to your team: custom rules, prompts, style guides, per-path config. | ●●●●● Plugin & skills | ●●●●● Presets & automations |
Privacy Whether your code stays on your own infrastructure: fully local, self-hostable, or cloud API only. | ●●●●● Fully local | ●●●●● Fully local possible |
Model freedom Whether you can point it at any provider, or it is wired to one. | ●●●●● BYOK + local | ●●●●● Bring-your-own-key |
Setup ease What it takes to get a first useful run out of it. | ●●●●● One-command start | ●●●●● One-command start |
Which one to pick
Pick DeepTutor if…
Privacy-first — run locally or with your own API keys while getting a production-grade, extensible tutoring stack (agents, RAG, persistent memory, and Skills marketplace).
Pick nanobot if…
Self-hosted — run a lightweight, extendable personal agent locally (or with your own API keys) that includes WebUI, long-term memory, and automation for persistent workflows.
What people want from each one
HKUDS/DeepTutor
Hacker News: DeepTutor: Agent-Native Personalized Tutoring drew 2 points and 0 comments.
HKUDS/nanobot
Hacker News: Nanobot: Ultra-Lightweight Alternative to OpenClaw drew 257 points and 128 comments.
Questions people ask
Is DeepTutor better than nanobot?
Neither one leads on the six capability axes, so the choice comes down to which of them fits the way you already work. DeepTutor is worth picking when privacy-first — run locally or with your own API keys while getting a production-grade, extensible tutoring stack (agents, RAG, persistent memory, and Skills marketplace).
Which of DeepTutor and nanobot keeps my code private?
DeepTutor: Fully local (5/5). nanobot: Fully local possible (5/5).
What does each one cost to run?
DeepTutor: Free to self-host; uses your model API key or local LLMs. nanobot: Your API key; optional paid hosting.
Full profiles: HKUDS/DeepTutor and HKUDS/nanobot. Everything else in Personal assistants.