Autonomous AI agent orchestrator — Codex, GPT, OpenRouter (any model), local models (Ollama/LM Studio), and Claude Code (
claude -p)
💬 Help shape OpenSwarm. Share feature ideas, vote on the roadmap, and ask questions in GitHub Discussions. The roadmap is built in the open — your feedback decides what ships next.
OpenSwarm orchestrates multiple AI agents as autonomous code workers. It picks up issues from Linear or a built-in local tracker, runs Worker/Reviewer pair pipelines, reports through a pluggable notifier (Discord, Slack, Telegram, webhook), and retains long-term memory via LanceDB. Workers run on OpenAI Codex/GPT, any OpenRouter model, local open-source models (Ollama, LM Studio), or Claude Code (claude -p, opt-in) — with cost-aware routing measured on an L0–L6 benchmark ladder.
Verified on real GitHub issues: the agentic harness solves SWE-bench Lite instances graded by the official harness. Hybrid mode — a frontier model diagnoses read-only, a lightweight model implements with a verification loop — resolved 3/3 attempted instances that every single lightweight model had failed, at a fraction of frontier-only cost. Workers also learn each repository over time: task outcomes are stored as per-repo knowledge and recalled into future prompts. (
OpenSwarm is proudly supported by Atlas Cloud — an enterprise AI infrastructure platform serving fast, stable LLM, image, and video APIs (partnered with OpenRouter and SGLang).
As an official provider sponsor, Atlas Cloud ships as the built-in atlascloud adapter (OpenAI-compatible Chat Completions, ATLASCLOUD_API_KEY) and provides ongoing monthly API credits that keep the project's autonomous runs going. To run OpenSwarm on Atlas Cloud, grab a key at atlascloud.ai, set ATLASCLOUD_API_KEY, and select adapter: atlascloud.