OpenHands

What is OpenHands?

OpenHands is an open-source, model-agnostic platform for building and running autonomous AI coding agents. Formerly known as OpenDevin, it provides a Software Agent SDK, CLI, web GUI, and hosted cloud service for software engineering tasks like writing code, fixing bugs, reviewing pull requests, and migrating legacy codebases. With 71,000+ GitHub stars, MIT licensing, and support for dozens of LLM providers, OpenHands works as the leading self-hostable alternative to proprietary coding agents like Devin or GitHub Copilot.

Key Features

• Software Agent SDK: A composable Python library for defining and running agents locally or at scale, with model-agnostic orchestration through the litellm library
• Sandboxed Execution: All code runs inside secure Docker containers, so agents can write, test, and iterate on code without risking your local environment
• Model-Agnostic Support: Works with OpenAI, Anthropic Claude, Google Gemini, local models through Ollama or vLLM, and 75+ other providers through litellm
• GitHub and GitLab Integration: Agents clone repositories, create branches, push commits, and open pull requests directly within existing repo workflows
• Local GUI and CLI: A browser-based React interface with embedded VS Code editor, terminal access, and a separate CLI for terminal-first workflows
• OpenHands Cloud: Hosted deployment at app.all-hands.dev with Slack, Jira, and Linear integrations, plus a free tier with 10 daily conversations
• Skills System: Specialized prompts with domain-specific knowledge that let teams adapt agents to particular workflows without rebuilding core logic
• SWE-Bench Performance: Resolves 53%+ of real-world GitHub issues on SWE-bench Verified when paired with strong models, scoring 77.6 on the benchmark

Use Cases

• Engineering teams handling maintenance backlogs: Use OpenHands to automate repetitive tasks like fixing merge conflicts, resolving linter failures, refactoring modules, and triaging GitHub issues across multiple repositories
• Backend developers migrating legacy codebases: Run agents to navigate large codebases, convert code between languages (COBOL to Java, for example), and test changes across multiple modules with limited manual work
• DevOps teams running automated security workflows: Set up agents for vulnerability scanning that automatically generate pull requests with fixes, integrated into existing CI/CD pipelines
• Solo developers prototyping applications: Use the Planning Agent to scope features from a high-level prompt, review a generated plan, then let the agent handle implementation, testing, and debugging
• Not ideal for: Non-technical users who need point-and-click automation (use Make, Zapier, or n8n instead) or teams that need pre-tuned domain-specific agents with strict compliance requirements

Strengths and Weaknesses

Strengths:

• Fully open-source with MIT licensing, so teams can self-host, audit, and modify without vendor lock-in
• Model-agnostic design means you can swap between cloud providers or run local models based on cost and privacy needs
• Active development with 71,000+ stars, 490+ contributors, and monthly releases including recent additions like Plan Mode and slash menus
• Sandboxed Docker execution keeps agent actions isolated and auditable, a real advantage for enterprise security requirements
• The free open-source tier has no conversation limits, and the cloud individual tier starts at $0 with pay-as-you-go LLM usage at cost

Weaknesses:

• Not fully autonomous yet, as users report needing to provide corrections and guidance during longer tasks
• Sandbox setup can be tricky, with reports of crashes and outdated documentation after the v0.10 release
• Rapid release cadence has introduced breaking changes in agent protocols, which can frustrate teams on older versions
• Error messages are sometimes vague, including reports of tasks failing without useful tracebacks
• The free cloud tier is limited to 1 workspace and 10 daily conversations

Pricing

• Open Source: Free. Local deployment for 1 user with unlimited daily conversations. Includes the OpenHands agent, web GUI, Terminal UI, CLI, Git integrations, and community support. Bring your own API key for any supported model.
• Cloud Individual: Free. SaaS for 1 user with 10 daily conversations. Adds hosted cloud access on desktop and mobile, API support, Jira and Slack integrations, MCP support, and Cloud Agent SDK. Use your own key or OpenHands models at cost with no markup. Credits start at $10.
• Cloud Growth: $500/month. SaaS for unlimited users. Adds multi-user RBAC, centralized team billing, shared projects and agents, and ticket-based support.
• Enterprise: Contact sales. Available as SaaS or self-hosted in a private VPC. Includes SAML/SSO, Large Codebase SDK, priority support with a named engineer, and a shared Slack channel.

New cloud users may receive $20 in free credits for a limited time. Student, nonprofit, and YC discount programs are available.

FAQ

Is OpenHands free?

Yes. The open-source version is completely free with no conversation limits. The cloud individual tier is also free with 10 daily conversations and pay-as-you-go LLM costs at provider rates with no markup.

What was OpenHands previously called?

OpenHands was previously called OpenDevin. The project rebranded and has since grown to 71,000+ GitHub stars.

Does OpenHands support local models?

Yes. OpenHands works with local models through Ollama, vLLM, and any provider supported by litellm. You can run it entirely on your own infrastructure with no external API calls.

How does OpenHands compare to Cursor?

OpenHands handles autonomous, long-running software engineering tasks in a sandboxed environment with support for 75+ LLM providers. Cursor is better for IDE-based coding with deep codebase indexing and real-time suggestions. Choose OpenHands for agent-driven automation; choose Cursor for daily editing.

Can OpenHands run code safely?

Yes. All code execution happens inside secure Docker containers. The sandbox isolates agent actions from your host system, and enterprise deployments can run in private VPCs with full RBAC controls.

How do I install OpenHands?

Clone the GitHub repo, run make build and make dev with Docker. On first launch, configure your LLM API key and model. Most developers report getting a working setup in 15 to 30 minutes.