OpenHands vs SWE-agent
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
A self-hosted control panel that runs AI coding agents on your machine, in Docker, or in the cloud.
Open source · MIT
An AI agent that tries to fix GitHub issues automatically, using the language model you choose.
The short answer
Choose OpenHands if you need…
- Developers who want coding agents running on a server while their laptop is off
- Teams that want a shared agent server for tasks like code review or dependency updates
- People who want to connect agents to Slack, GitHub, or Linear through automations
- Users who want to choose their own LLM provider
Choose SWE-agent if you need…
- Researchers studying autonomous coding agents or running SWE-bench experiments
- Developers who want to experiment with an LLM attempting issue fixes in their own repositories
- Students learning how agent-computer interfaces work, since the README describes it as simple and hackable
- People who want a configurable agent controlled by a single YAML file
Side-by-side
| OpenHands | SWE-agent | |
|---|---|---|
| Type | App | AI model / agent |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 92.5k | 20.7k |
| Setup difficulty | Intermediate | Intermediate |
| How you get it | Install with a package manager | Clone and build from source |
| Main language | TypeScript | Python |
| Last code update | 4 days ago | 10 days ago |
What each one is
OpenHands
Agent Canvas is a self-hosted control center for AI coding agents. You start conversations with agents and set up automations, such as generating reports that publish to Slack or breaking GitHub issues into tasks. It runs on your own machine by default and can also connect to agents running in Docker, on virtual machines, or on OpenHands Cloud or Enterprise infrastructure. It can run the open source OpenHands agent or third-party agents such as Claude Code, Codex, and Gemini CLI.
SWE-agent
SWE-agent takes a GitHub issue and lets a language model you pick (the README mentions GPT-4o and Claude Sonnet 4 as examples) use tools to try to fix it in a real repository. It is also described as usable for offensive cybersecurity (capture-the-flag) challenges and custom coding tasks. It is a research project from Princeton and Stanford, and its README says its main development has moved to the simpler mini-SWE-agent.
Best for
OpenHands
- Developers who want coding agents running on a server while their laptop is off
- Teams that want a shared agent server for tasks like code review or dependency updates
- People who want to connect agents to Slack, GitHub, or Linear through automations
- Users who want to choose their own LLM provider
SWE-agent
- Researchers studying autonomous coding agents or running SWE-bench experiments
- Developers who want to experiment with an LLM attempting issue fixes in their own repositories
- Students learning how agent-computer interfaces work, since the README describes it as simple and hackable
- People who want a configurable agent controlled by a single YAML file
Strengths
OpenHands
- Self-hosted, so you control where agents run and where your work is stored
- Supports several agents and backends from one frontend
- Released under the MIT license with a large public community (about 92,000 stars)
SWE-agent
- The README reports state-of-the-art results on SWE-bench among open-source projects
- Configuration is handled by a single YAML file and the README says it is fully documented
- MIT licensed with a public docs site, Slack, and a Codespaces option to try it in a browser
Not ideal for
OpenHands
- People who need strong isolation by default: the quickstart without a sandbox gives the agent full access to your filesystem
- Non-technical users who are not comfortable with Node.js, npm, Docker, or the command line
- Anyone who needs a fully hosted service with no setup, since the README centers on self-hosting
SWE-agent
- Teams wanting the project's actively recommended tool: the README says most development has moved to mini-SWE-agent, which it recommends instead
- Anyone needing a polished, finished product: the project is framed as research code
- People who cannot pay for or access a language model API, since the README assumes you bring your own model
Trade-offs
OpenHands
- Running without a sandbox gives the agent full access to your filesystem, so the Docker options need careful setup
- Multiple features depend on configuring backends, LLM keys, and integrations, which takes effort
- The README is truncated and does not fully document security hardening or every integration; see the linked docs
SWE-agent
- The README says mini-SWE-agent has superseded it and is recommended instead going forward
- The EnIGMA cybersecurity mode currently points users to older version 0.7 rather than 1.0
- Results depend on the language model and API you supply; the README does not state costs or hardware needs
Getting started
OpenHands
Install globally with npm (no sandbox)
npm install -g @openhands/agent-canvasStart the full local stack
agent-canvasSWE-agent
Clone the repository
git clone https://github.com/SWE-agent/SWE-agent.gitFrequently asked questions
What is the difference between OpenHands and SWE-agent?
OpenHands: A self-hosted control panel that runs AI coding agents on your machine, in Docker, or in the cloud. SWE-agent: An AI agent that tries to fix GitHub issues automatically, using the language model you choose. OpenHands suits developers who want coding agents running on a server while their laptop is off, while SWE-agent suits researchers studying autonomous coding agents or running swe-bench experiments.
Are OpenHands and SWE-agent free?
OpenHands: Free and open source. SWE-agent: Free and open source.
Is OpenHands or SWE-agent more popular?
OpenHands has more GitHub stars (92.5k) than SWE-agent (20.7k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to OpenHands and SWE-agent?
Other options people compare them with include One API, LlamaGPT, codex-chatgpt-web, wechat-bot, GitDiagram.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.