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openevolve

Evolves programs with LLM mutations, scored by your own evaluator

Stars
7.5k
License
Apache-2.0
Last commit
Oct 2026
Last release
Sep 2026
Language
Python

Missed the latest GitHub check; these facts may be older.

Overview

OpenEvolve takes an initial program and an evaluator function, then repeatedly asks LLMs to rewrite the code. It keeps candidates in a MAP-Elites population split across islands. It works with OpenAI-compatible APIs, local servers such as Ollama, or the Claude Code, Copilot and Codex CLIs as backends. It runs from the command line or as a Python library.

Who it is for: Engineers and researchers optimizing algorithms or kernels against a score

Strengths

  • MAP-Elites with multiple islands and migration, plus island-selector and population hooks
  • Works with OpenAI-compatible APIs, Ollama/vLLM, and Claude Code, Copilot or Codex CLIs
  • Usable as a CLI or a Python library with inline code and callable evaluators
  • Seeded by default (seed 42); cascade evaluation filters weak programs early

Weaknesses

  • Needs a user-written evaluator; it does not work on an arbitrary repo by itself
  • LLM cost is real: README estimates $0.01-0.60 per iteration depending on model
  • Benchmark claims in the README are not backed by numbers beyond the examples
  • Quick start sets a Gemini key through OPENAI_API_KEY, which is confusing

What it needs

  • no GPU
  • Docker
  • Needs Python 3.10+, LLM provider (OpenAI-compatible API or Claude Code/Copilot/Codex CLI)
  • Models: OpenAI, Google Gemini, Ollama, vLLM, OptiLLM

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