ray vs ray-llm

Common questions

What is the difference between ray and ray-llm?

ray: Unified framework for scaling AI and Python applications. ray-llm: Archived repository for LLMs on Ray, now integrated into Ray.. See the comparison table for live GitHub stats and shared categories.

When should I choose ray over ray-llm?

Choose ray over ray-llm when Tags unique to ray: data-science, deep-learning, deployment, distributed; Also covers Developer Tools, Evaluation & Observability; When you need to perform distributed training, as Ray's Train library simplifies the setup and management of distributed training jobs.

When should I choose ray-llm over ray?

Choose ray-llm over ray when Pricing: Pricing details are not available.; Requirements: Ensure you have the latest version of Ray installed to use the ray.serve.llm and ray.data.llm APIs.; Tags unique to ray-llm: llm, llm-serving, ray; If you are working with Ray and need to deploy large language models, use the ray.serve.llm and ray.data.llm APIs, which are now integrated into the Ray framework.

When should I avoid ray?

If your project is limited to single-node development and does not require scaling across multiple machines or clusters. When the specific requirements of your project are better met by specialized tools that offer more tailored functionality for a particular task, such as TensorFlow for deep learning or PyTorch for GPU If you are working in a non-Python environment, as Ray is primarily designed for Python applications.

When should I avoid ray-llm?

Do not use the archived Ray-LLM repository for active development or deployment, as it is no longer maintained and its functionalities have been integrated into the Ray framework. If you require the latest features and support for deploying large language models, avoid the archived repository and use the ray.serve.llm and ray.data.llm APIs directly.

Is ray or ray-llm more popular on GitHub?

ray has more GitHub stars (43,863 vs 1,261). Stars measure visibility, not whether either tool fits your constraints.

Are ray and ray-llm open source?

Yes - both are open-source projects on GitHub.

Where can I find alternatives to ray or ray-llm?

GraphCanon lists graph-backed alternatives at ray alternatives and ray-llm alternatives (ray markdown twin, ray-llm markdown twin), ranked by typed relationship edges rather than popularity votes.

Is there a machine-readable version of this comparison?

Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

Which is better maintained, ray or ray-llm?

ray: Very active. ray-llm: Archived. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance.

Where are the full trust reports for ray and ray-llm?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ray trust report; ray-llm trust report.