Ross ROSS = Recommend OSS · open-source software intelligence for agents

algorithmicsuperintelligence/openevolve

Open-source implementation of AlphaEvolve observed · 2026-10-11

github.com/algorithmicsuperintelligence/openevolve · Python · Apache-2.0 (permissive) observed · 2026-10-11

Health v2 · maintenance only

86/100

  • Activity 99
  • Release rhythm 97
  • Longevity 37
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.

  • gap_med: 2
  • age_days: 523
  • days_rel: 23
  • days_push: 10
  • n_releases_24m: 56

Full methodology

Adoption not part of the score

7518 stars · 1180 forks observed · 2026-10-11

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

OpenEvolve is an open-source Python implementation of DeepMind's AlphaEvolve, an evolutionary coding agent that uses LLM ensembles to autonomously discover and optimize algorithms. It evolves code through iterative refinement with parallel island-based evolution, multi-objective Pareto optimization, and evaluation pipelines.

Use cases

  • automatically optimize slow Python functions for speed
  • discover new algorithms for math problems like circle packing
  • evolve GPU kernels and Metal shaders for better performance
  • use LLMs to iteratively refine and improve existing code
  • run evolutionary search over code with multiple objectives
  • find state-of-the-art solutions to scientific computing problems

When to choose

  • you want LLM-driven autonomous code optimization without human guidance
  • you need reproducible evolutionary search over program code
  • you want to reproduce or extend AlphaEvolve-style algorithm discovery
  • you need multi-objective optimization of code with parallel evaluation

When to avoid

  • you need simple deterministic code refactoring rather than evolutionary search
  • your task lacks a programmable evaluation metric to score candidate programs
  • you cannot afford the LLM API costs of large population-based search
  • you need guaranteed correctness rather than best-effort discovered solutions

Facets

library · maturity active

llm-inference agent-framework machine-learning developer-tools artificial-intelligence large-language-models python cross-platform cli evolutionary-algorithms genetic-algorithms alphaevolve code-optimization llm-ensemble prompt-evolution map-elites ai-agents algorithms automation

1 source

Member repositories

RepositoryRoleHealth v2
algorithmicsuperintelligence/openevolvemain86

For agents

markdown · JSON · MCP: product_card(name="algorithmicsuperintelligence/openevolve")

Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem