ray-project/ray vs stas00/ml-engineering
Compare ray-project/ray and stas00/ml-engineering using the current verified snapshot: positioning, license, deployment, use cases, limitations, and original sources.
ray-project/ray
A unified framework for scaling Python and AI applications from a single laptop to a cluster. It provides distributed abstractions for tasks, actors, and objects, alongside libraries for data processing, training, tuning, reinforcement learning, and serving.
- License
- Apache-2.0
- Deployment
- Refer to project documentation
- Use cases
- AI engineers and developers who need to scale Python applications across a cluster.
- Updated
- 2026-07-17T07:57:18Z
stas00/ml-engineering
An open collection of methodologies, scripts, and step-by-step instructions for training, fine-tuning, and debugging large language models and multi-modal models. The material is designed for practitioners who need consolidated know-how and copy-n-paste solutions.
- License
- CC-BY-SA-4.0
- Deployment
- Refer to project documentation
- Use cases
- AI engineers and researchers who already possess technical knowledge of LLM/VLM training engineering and need consolidated, applied methodologies.
- Updated
- 2026-07-17T12:27:57Z
How to choose
First eliminate options that fail required deployment, license, or use-case constraints; then inspect each detail page for limitations and direct evidence.