Openevolve — AI Agent Review & Live Stats

Live GitHub stats, community sentiment, and trend data for Openevolve. TrendingBots tracks star velocity, fork activity, and what developers are saying — updated from real data sources.

GitHub data synced: Mar 18, 2026 • Sentiment updated: Unknown

GitHub Statistics

Why Openevolve Stands Out

OpenEvolve is valuable because it provides an open-source implementation of AlphaEvolve, allowing users to leverage the power of evolutionary algorithms for autonomous code optimization. Its ability to discover entirely new algorithms without human guidance sets it apart from alternative optimization methods. By using OpenEvolve, users can achieve state-of-the-art results in various domains, including GPU optimization, mathematical optimization, and algorithm design.

Built With

Build a GPU-optimized kernel for machine learning workloads — OpenEvolve's evolutionary algorithms can discover hardware-aware optimizations, Build an autonomous coding agent that discovers breakthrough algorithms — OpenEvolve's LLMs can create new algorithms without human guidance, Build a state-of-the-art circle packing solution — OpenEvolve's iterative refinement process can achieve optimal results, Build an adaptive sorting algorithm — OpenEvolve's evolutionary computation can create efficient sorting algorithms, Build a multi-language code optimization framework — OpenEvolve supports optimization of code in multiple languages, including Python, Rust, and R

Getting Started

  1. Install OpenEvolve using pip: `pip install openevolve`
  2. Set up your OpenAI API key: `export OPENAI_API_KEY='your-gemini-api-key'`
  3. Configure your evolution settings: modify the `config.yaml` file to suit your needs
  4. Run your first evolution: `python openevolve-run.py examples/function_minimization/initial_program.py examples/function_minimization/evaluator.py --config examples/function_minimization/config.yaml --iterations 50`
  5. Try evolving a simple function to verify it works: use the `evolve_function` API to optimize a Python function, such as the `bubble_sort` example

About

Open-source implementation of AlphaEvolve

Category & Tags

Category: coding

Tags: alpha-evolve, alphacode, alphaevolve, coding-agent, deepmind, deepmind-lab, discovery, distributed-evolutionary-algorithms, evolutionary-algorithms, evolutionary-computation, genetic-algorithm, genetic-algorithms, iterative-methods, iterative-refinement, llm-engineering, llm-ensemble, llm-inference, openevolve, optimize