--- title: "ollama vs ray-llm" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ollama-ollama-vs-ray-project-ray-llm" tools: ["ollama-ollama", "ray-project-ray-llm"] --- # ollama vs ray-llm *GraphCanon updated Jul 12, 2026* ## Verdict Pick ollama when ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers; pick ray-llm when tags unique to ray-llm: ray, llm, llm-serving. [ollama](https://ollama.com) reports 176k GitHub stars, 17k forks, and 3.4k open issues, last pushed Jul 10, 2026. [ray-llm](https://docs.ray.io/en/latest/) has 1.3k stars, 90 forks, and 0 open issues, last pushed Mar 13, 2025. Figures are from public GitHub metadata via [ollama's repository](https://github.com/ollama/ollama) and [ray-llm's repository](https://github.com/ray-project/ray-llm). | | [ollama](/tools/ollama-ollama.md) | [ray-llm](/tools/ray-project-ray-llm.md) | | --- | --- | --- | | Tagline | Get up and running with various large language models using Ollama. | RayLLM - LLMs on Ray (Archived). Read README for more info. | | Stars | 175,936 | 1,263 | | Forks | 16,939 | 90 | | Open issues | 3,423 | 0 | | Language | Go | - | | Adopt for | Ollama is a Go-based platform that provides tools for deploying and managing large language models (LLMs) like Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma using docker images, package managers, cloud and | - | | Persona | - | - | | Runtime | - | - | | License | MIT license - permissive open-source licensing that allows for broad use of the tool. | - | | Categories | LLM Frameworks, Inference & Serving | LLM Frameworks, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ollama](/tools/ollama-ollama.md) | [ray-llm](/tools/ray-project-ray-llm.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Archived (8%) | | Days since push | 1d | 485d | | Archived on GitHub | No | Yes | | Open issues (now) | 3.4k | 0 | | Security scan | 52 low (52 low) | No lockfile | | Full report | [trust report](/tools/ollama-ollama/trust.md) | [trust report](/tools/ray-project-ray-llm/trust.md) | ## Decision facts: ollama - **Hosting:** self hosted - Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers. - **Adopt for:** Ollama is a Go-based platform that provides tools for deploying and managing large language models (LLMs) like Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma using docker images, package managers, cloud and - **License detail:** MIT license - permissive open-source licensing that allows for broad use of the tool. ## Choose when ### Choose ollama if… - Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers. - Tags unique to ollama: go, llms, llama, mistral. - ollama ships Docker support for self-hosted deployment. - Use Ollama when you require a multi-model platform supporting several large language models such as Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and intend to deploy in various cloud or ### Choose ray-llm if… - Tags unique to ray-llm: ray, llm, llm-serving. - Leaner open-issue backlog (0). ## When NOT to use ollama - Avoid using Ollama if you are only interested in a single LLM deployment and seek simplified, model-specific solutions with tailored support rather than a comprehensive multi-model platform. ## When NOT to use ray-llm - ray-llm is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## Common questions ### What is the difference between ollama and ray-llm? ollama: Get up and running with various large language models using Ollama.. ray-llm: RayLLM - LLMs on Ray (Archived). Read README for more info.. See the comparison table for live GitHub stats and shared categories. ### When should I choose ollama over ray-llm? Choose ollama over ray-llm when Ollama supports self-hosted and cloud-deployable models using Docker, Helm charts, and various package managers; Tags unique to ollama: go, llms, llama, mistral; ollama ships Docker support for self-hosted deployment; Use Ollama when you require a multi-model platform supporting several large language models such as Kimi-K2.6, GLM-5.1, MiniMax, DeepSeek, gpt-oss, Qwen, Gemma and intend to deploy in various cloud or. ### When should I choose ray-llm over ollama? Choose ray-llm over ollama when Tags unique to ray-llm: ray, llm, llm-serving; Leaner open-issue backlog (0). ### When should I avoid ollama? Avoid using Ollama if you are only interested in a single LLM deployment and seek simplified, model-specific solutions with tailored support rather than a comprehensive multi-model platform. ### When should I avoid ray-llm? ray-llm is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### Is ollama or ray-llm more popular on GitHub? ollama has more GitHub stars (175,936 vs 1,263). Stars measure visibility, not whether either tool fits your constraints. ### Are ollama and ray-llm open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to ollama or ray-llm? GraphCanon lists graph-backed alternatives at [ollama alternatives](/tools/ollama-ollama/alternatives) and [ray-llm alternatives](/tools/ray-project-ray-llm/alternatives) ([ollama markdown twin](/tools/ollama-ollama/alternatives.md), [ray-llm markdown twin](/tools/ray-project-ray-llm/alternatives.md)), 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](/compare/ollama-ollama-vs-ray-project-ray-llm.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ollama or ray-llm? ollama: 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 ollama and ray-llm? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ollama trust report](/tools/ollama-ollama/trust); [ray-llm trust report](/tools/ray-project-ray-llm/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ollama-ollama`](/api/graphcanon/graph?tool=ollama-ollama) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_