OpenClaw vs AutoGPT
A side-by-side comparison to help you choose the right tool.
82
OpenClaw scores higher overall (82/100)
But the best choice depends on your specific needs. Compare below.
| Feature | OpenClaw | AutoGPT |
|---|---|---|
| Our score | 82 | 65 |
| Pricing | Free and open-source (MIT license). Managed cloud hosting at $59/month. Self-hosted infrastructure costs typically $6-50/month depending on usage. | Free and open-source. Requires your own API keys for underlying LLM providers. Cloud-hosted version in development. |
| Free plan | Yes | Yes |
| Best for | Developers comfortable with self-hosted infrastructure, Teams that need private, on-premise AI agent automation, Power users who want to connect AI to 50+ messaging and business tools, Organizations prioritizing data privacy over convenience | developers and researchers experimenting with autonomous AI agents, technical users who want to automate multi-step research workflows, AI enthusiasts exploring the boundaries of agent-based systems, teams prototyping agent-based automation before building custom solutions |
| Platforms | mac, linux, web | desktop, web |
| API | Yes | No |
| Languages | en | en |
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| Visit site | Visit site |
OpenClaw
82
- Pricing
- Free and open-source (MIT license). Managed cloud hosting at $59/month. Self-hosted infrastructure costs typically $6-50/month depending on usage.
- Free plan
- Yes
- Best for
- Developers comfortable with self-hosted infrastructure, Teams that need private, on-premise AI agent automation, Power users who want to connect AI to 50+ messaging and business tools, Organizations prioritizing data privacy over convenience
- Platforms
- mac, linux, web
- API
- Yes
- Languages
- en
AutoGPT
65
- Pricing
- Free and open-source. Requires your own API keys for underlying LLM providers. Cloud-hosted version in development.
- Free plan
- Yes
- Best for
- developers and researchers experimenting with autonomous AI agents, technical users who want to automate multi-step research workflows, AI enthusiasts exploring the boundaries of agent-based systems, teams prototyping agent-based automation before building custom solutions
- Platforms
- desktop, web
- API
- No
- Languages
- en
82Choose OpenClaw if:
- You are Developers comfortable with self-hosted infrastructure
- You are Teams that need private, on-premise AI agent automation
- You are Power users who want to connect AI to 50+ messaging and business tools
- You want to start free
65Choose AutoGPT if:
- You are developers and researchers experimenting with autonomous AI agents
- You are technical users who want to automate multi-step research workflows
- You are AI enthusiasts exploring the boundaries of agent-based systems
- You want to start free
FAQ
- What is the difference between OpenClaw and AutoGPT?
- OpenClaw is openclaw is a free, open-source ai agent platform that runs autonomously across messaging apps and developer tools. it is the fastest-growing open-source project in history, best suited for technical users who want full control over their ai automation stack. AutoGPT is open-source autonomous ai agent framework that chains together llm calls to complete multi-step tasks independently, pioneering the concept of self-directed ai agents.
- Which is cheaper, OpenClaw or AutoGPT?
- OpenClaw: Free and open-source (MIT license). Managed cloud hosting at $59/month. Self-hosted infrastructure costs typically $6-50/month depending on usage.. AutoGPT: Free and open-source. Requires your own API keys for underlying LLM providers. Cloud-hosted version in development.. OpenClaw has a free plan. AutoGPT has a free plan.
- Who is OpenClaw best for?
- OpenClaw is best for Developers comfortable with self-hosted infrastructure, Teams that need private, on-premise AI agent automation, Power users who want to connect AI to 50+ messaging and business tools, Organizations prioritizing data privacy over convenience.
- Who is AutoGPT best for?
- AutoGPT is best for developers and researchers experimenting with autonomous AI agents, technical users who want to automate multi-step research workflows, AI enthusiasts exploring the boundaries of agent-based systems, teams prototyping agent-based automation before building custom solutions.