8 Best OpenHands Alternatives in 2026 (Open Source)

OpenHands — 🙌 OpenHands: AI-Driven Development. OpenDevin is the original name of what is now OpenHands — the same project that achieves 77.6% on SWE-Bench, now maintained under All-Hands-AI/OpenHands with expanded enterprise features

These 8 open-source tools do the same job. They are ordered by how closely they match OpenHands, with live GitHub data so you can see which projects are actively maintained.

ToolGitHub starsStars / 30dLast commit
OpenHands(original)89.6k+3,1602026-09-30
SWE-agent20.4k+2542026-07-16
Devika19.6k+92025-09-25
GPT PILOT33.7k+-242026-06-12
Claude Code148.7k+10,4592026-09-30
Codex127.4k+9,5312026-09-30
Cursor33.3k+1172026-05-12
Dev-GPT1.9k+-02023-06-26
DeerFlow83.3k+5,3432026-09-30
  1. 1. SWE-agent

    SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]

    What sets it apart: Princeton/Stanford research project achieving SoTA on SWE-bench — the most rigorous benchmark for automated software engineering — with a simple, hackable design that leaves maximal agency to the LLM

    Best for: Automated bug fixing and issue resolution in GitHub repos; Research on AI-driven software engineering capabilities

  2. 2. Devika

    Devika is the first open-source implementation of an Agentic Software Engineer. Initially started as an open-source alternative to Devin.

    What sets it apart: vs Devin / SWE-Agent: open-source AI software engineer with multi-LLM support (6+ providers including local Ollama) and visual state tracking — the most popular open-source Devin alternative

    Best for: Developers wanting an open-source Devin alternative for AI-assisted coding; Multi-LLM experimentation with AI software engineering tasks; Teams exploring autonomous code generation with human oversight

  3. 3. GPT PILOT

    The first real AI developer

    What sets it apart: vs Devin / Cursor / Claude Code: pioneered multi-agent development team architecture (Architect→Developer→Reviewer→Debugger) with incremental building and human-in-the-loop — designed to automate 95% of coding while keeping human oversight for the critical 5%

    Best for: Understanding multi-agent software development architecture; Building applications with human-AI collaborative iteration; Research on AI coding agent team designs

  4. 4. Claude Code

    Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows

    What sets it apart: Unlike Codex (OpenAI) which also runs in terminal, Claude Code has deeper codebase understanding via long-context and native GitHub integration with @claude mentions

    Best for: Developers who live in the terminal and want AI-assisted coding without leaving CLI; Teams using GitHub workflows who want automated PR reviews and code generation

  5. 5. Codex

    Lightweight coding agent that runs in your terminal

    What sets it apart: Unlike Claude Code (Anthropic-only), Codex uniquely integrates with existing ChatGPT subscriptions and offers both CLI and cloud-based (Codex Web) agent variants

    Best for: OpenAI ecosystem users wanting a terminal-first coding agent with ChatGPT plan integration; Teams already paying for ChatGPT Enterprise who want CLI-based code automation

  6. 6. Cursor

    The AI Code Editor

    What sets it apart: Unlike AI plugins added to existing editors, Cursor is built from the ground up as an AI-native editor with deep codebase indexing and multi-file context — providing more coherent AI assistance than bolt-on extensions like GitHub Copilot

    Best for: Individual developers and small teams wanting AI-integrated IDE experience without plugin setup; VS Code users who want seamless AI coding without switching to a separate tool

  7. 7. Dev-GPT

    Your Virtual Development Team

    What sets it apart: vs Copilot/Cursor: generates complete microservices from descriptions with iterative testing until they pass — handles Dockerfile, testing, error recovery, and cloud deployment as a pipeline, not just code completion

    Best for: Rapid prototyping of utility microservices; Auto-generating and deploying simple API endpoints; Data processing and media transformation services

  8. 8. DeerFlow

    An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of ta

    What sets it apart: vs AutoGPT: purpose-built for deep research with sub-agent orchestration and sandbox; vs LangGraph: higher-level harness with built-in memory, sandbox, and skill system rather than bare graph framework

    Best for: Deep research and exploration tasks; Building multi-agent systems with sub-agent orchestration; Teams wanting coding agent integration (Claude Code/Codex)