# Ray

> Distributed compute engine for AI

Scale Python and ML workloads across clusters for training, tuning and serving.

- Source: https://github.com/ray-project/ray
- Homepage: https://ray.io
- License: Apache-2.0
- Language: Python
- Stars: 43967
- Forks: 8111
- Contributors: 1620
- Last commit: 2026-10-03
- Latest release: ray-2.59.0 (2026-10-02)
- Purpose: AI & LLM tooling, Infra & DevOps
- Runs on: Library / SDK
- For: Enterprise

## Worth score: 84/100

How much DigGitHub recommends it, from activity, adoption, docs, license and security signals.

- Popularity: 23/25
- Momentum: 10/20
- Maintenance: 25/25
- Community: 15/15
- Readiness: 11/15

## Alternatives

- [Keras](https://diggithub.com/keras-team/keras.md): Deep learning for humans
- [PennyLane](https://diggithub.com/PennyLaneAI/pennylane.md): Quantum computing and quantum machine learning in Python
- [TensorFlow](https://diggithub.com/tensorflow/tensorflow.md): Google's end-to-end machine learning framework
- [Supervision](https://diggithub.com/roboflow/supervision.md): Reusable computer vision tools
- [ncnn](https://diggithub.com/Tencent/ncnn.md): Neural network inference for mobile
- [Ludwig](https://diggithub.com/ludwig-ai/ludwig.md): Low-code framework for custom AI models
- [vLLM](https://diggithub.com/vllm-project/vllm.md): High-throughput LLM serving engine
- [Oumi](https://diggithub.com/oumi-ai/oumi.md): Fine-tune, evaluate and deploy open models

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Source page: https://diggithub.com/ray-project/ray
Updated: 2026-10-04