Head to Head

nanobot vs OpenClaw

nanobot and OpenClaw compared on where they run, how your team reaches them, capabilities, live momentum and cost.

Tools for AI Builders—All the hardware and tools you need to run private AI at your office or at home.Shop Now

nnanobot

OOpenClaw

Profile

Runs

Self-Hosted

Self-Hosted, Desktop

Where You Talk to It

Telegram, Slack, Discord, Teams, Email, Web, CLI

WhatsApp, Telegram, Slack, Discord, Teams, Web, CLI, Desktop

License

MIT

Pricing

Free and open source (MIT). You pay only for the models you connect.

Free and open source (MIT). You pay for the model provider and the hardware you run it on.

Maintained by

HKUDS (University of Hong Kong Data Intelligence Lab)

OpenClaw Foundation

Best for

Teams that want a readable Python agent they can extend

Technical teams that want a self-hosted assistant across every chat app

Live Data

GitHub Stars

48.8K

–

Last Commit

Today

—

Vendor Status

–

Price per 1M Tokens (In / Out)

–

Capabilities

Local Models

Cloud Models

MCP Support

Strengths

Small, readable Python core that is easy to inspect and extend.
Built-in web UI, so first setup does not require config files.
Works with cloud APIs and local models, with fallback models.
Includes a Python SDK and an OpenAI-compatible API for integrations.

The largest community and skill ecosystem of any open source assistant.
Works in the chat apps your team already uses, from WhatsApp to Teams.
Model agnostic: use Claude, OpenAI models or local models and switch without rework.
Memory, credentials and state stay on your own hardware.
Run by an independent non-profit foundation, not a single vendor.

Trade-offs

Needs Python 3.11 or newer and some technical setup to run as a service.
Fast release pace, so features and settings change often.
Shell and file tools need careful access settings on shared machines.

Researchers have found well over 100,000 instances exposed to the internet with unsafe settings.
Hundreds of malicious skills were found on ClawHub, its community marketplace, including password stealers.
Tools run directly on the host unless you configure sandboxing yourself.
A large codebase with many settings, so setup and hardening take real effort.

Key Differences

OpenClaw is the more mature project, first released in 2025. nanobot followed in 2026.

Head to Head in Numbers

Live data from GitHub and the package registries, refreshed every day.

GitHub stars

nanobot: 48.8K
OpenClaw: –

Contributors

nanobot: 463
OpenClaw: –

Which One Should You Pick?

nanobot

Pick nanobot if you need: Teams that want a readable Python agent they can extend

Full nanobot profile

OpenClaw

Pick OpenClaw if you need: Technical teams that want a self-hosted assistant across every chat app

Full OpenClaw profile

Back to All AI Agents

More AI Agent Comparisons

Monthly Report

The AI Build ReportSeptember 2026

Which models lead, where API prices moved, and what it costs to run them. Measured from live data.

Cover of The AI Build Report, the free monthly snapshot of AI models, prices and hardware

Frequently Asked Questions

Straight answers to the questions we hear most often.

Can't find what you're looking for? Book a Discovery Call

Which is older, nanobot or OpenClaw?

OpenClaw was first released in 2025 and nanobot in 2026. A longer track record usually means more examples, integrations and answered questions.

What is the main difference between nanobot and OpenClaw?

nanobot runs as self-hosted. OpenClaw runs as self-hosted, desktop. That choice decides where your data lives, who maintains the agent and how fast you can roll it out.

Is nanobot or OpenClaw cheaper?

nanobot is open source and OpenClaw is open source. For both, the model bill usually matters more than the license. Use the agent cost calculator to estimate it for your workload.