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ray-project/ray

Inference Engines

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

8.6
GitHub Metrics
Stars
43.6k
Forks
8.0k
Open Issues
3.5k
Watchers
479
Contributors
1.7k
Weekly Commits
50
Language
Python
License
Apache-2.0
Last Commit
Aug 28, 2026
Created
Oct 25, 2016
Latest Release
ray-2.58.0
Release Date
Aug 23, 2026
Synced: Aug 28, 2026
Quality Scores
Documentation Qualityw: 20%
8.5

Has docs site (https://ray.io). Description: 128 chars. Stars signal: 43,630. Contributors: 1706. Score: 8.5/10

Community Healthw: 20%
9.0

Stars: 43,630. Contributors: 1706. Watchers: 479. Forks: 7,971. Issue ratio: 8.1%. Score: 9/10

Maintenance Velocityw: 15%
9.8

Last commit: 0d ago. Weekly commits: 43. Latest release: ray-2.58.0. Maturity bonus: 9.8y old. Score: 9.8/10

API Design & DXw: 20%
7.3

Stars/issues ratio: 12. Dynamic language: Python. Has documentation site. Permissive license: Apache-2.0. Popularity signal: 43,630 stars. Score: 7.3/10

Production Readinessw: 15%
8.8

Battle-tested: 43,630 stars. Peer review: 1706 contributors. Versioned: ray-2.58.0. Licensed: Apache-2.0. Age: 9.8 years. Maintenance: last commit 0d ago. Score: 8.8/10

Ecosystem Integrationw: 10%
8.9

Fork interest: 7,971. Major ecosystem: Python. Integration-friendly: Apache-2.0. Adoption: 43,630 stars. Has web presence. Score: 8.9/10

Tags
data-sciencedeep-learningdeploymentdistributedhyperparameter-optimizationhyperparameter-searchlarge-language-modelsllmllm-inferencellm-serving
Radar
Documentation Quality
Community Health
Maintenance Velocity
API Design & DX
Production Readiness
Ecosystem Integration
ray-project/ray — 8.6/10 — AI/LLM Repository Review — StackQuadrant