8 Best Devika Alternatives in 2026 (Open Source)

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

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

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

   ⭐ 20.4kDevika vs SWE-agent →Full profile →

2. 2. OpenHands

   🙌 OpenHands: AI-Driven Development

   What sets it apart: Unlike Claude Code and Codex (single-model CLI tools), OpenHands is model-agnostic with the highest SWE-Bench score (77.6%) and offers SDK, CLI, GUI, and enterprise deployment — a full-stack autonomous developer platform

   Best for: Engineering teams wanting an autonomous coding agent that can resolve real GitHub issues end-to-end; Enterprises needing self-hosted AI developer tools with Jira/Slack integration

   ⭐ 89.6kDevika vs OpenHands →Full profile →

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

   ⭐ 33.7kDevika vs GPT PILOT →Full profile →

4. 4. MetaGPT

   🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming

   What sets it apart: vs AutoGen/CrewAI: models entire software company with role-based SOPs (PM→Architect→Engineer), producing not just code but docs, API specs, and data structures

   Best for: Automated software project generation from requirements; Research on multi-agent collaboration and SOP-driven workflows

   ⭐ 70.7kDevika vs MetaGPT →Full profile →

5. 5. ChatDev

   ChatDev 2.0: Dev All through LLM-powered Multi-Agent Collaboration

   What sets it apart: Pioneered the virtual software company paradigm with role-based agents — v2.0 evolved into a general-purpose zero-code multi-agent platform

   Best for: Research on multi-agent collaboration and communication; Rapid prototyping of software via natural language descriptions

   ⭐ 34.4kDevika vs ChatDev →Full profile →

6. 6. gpt-engineer

   CLI platform to experiment with codegen. Precursor to: https://lovable.dev

   What sets it apart: vs Copilot/Cursor/aider: 'The OG code generation experimentation platform' — generates entire codebases from specs with extensible agent customization via preprompts, targeting researchers building coding agents

   Best for: Rapid prototyping from natural language specifications; Research on code generation agent architectures; Iterative code improvement with visual context (diagrams, mockups)

   ⭐ 55.1kDevika vs gpt-engineer →Full profile →

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

   ⭐ 1.9kDevika vs Dev-GPT →Full profile →

8. 8. DevOpsGPT

   Multi agent system for AI-driven software development. Combine LLM with DevOps tools to convert natural language requirements into working software. Supports any development language and extends the e

   What sets it apart: vs GPT-Engineer / Devin: end-to-end DevOps integration from requirements → code → CI/CD → deployment — not just code generation but full software delivery pipeline automation

   Best for: Teams wanting to automate software development from natural language specs; Rapid prototyping of APIs and web services from requirements; Organizations exploring AI-driven DevOps workflows

   ⭐ 6.0kDevika vs DevOpsGPT →Full profile →