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Comparison

ollama vs ray-llm

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.

Markdown twin · ollama alternatives · ray-llm alternatives

GraphCanon updated today

ollama logo

ollama

ollama/ollama

★ 176kpushed Jul 10, 2026
vs
ray-llm logo

ray-llm

ray-project/ray-llm

★ 1.3kpushed Mar 13, 2025

Trust & integrity

Signalollamaray-llm
Maintenance
Very active (1d since push)
As of today · github_public_v1
Archived (485d since push)
As of today · github_public_v1
Provenance
Not a fork · Organization account
As of today · github_public_v1
Not a fork · Organization account
As of today · github_public_v1
Security (OSV)
52 low (52 low)
As of today · osv@v1
No lockfile
As of today · none
ollama trust reportray-llm trust reportTrust methodology

Tagline

ollama
Get up and running with various large language models using Ollama.
ray-llm
RayLLM - LLMs on Ray (Archived). Read README for more info.

Stars

ollama
176k
ray-llm
1.3k

Forks

ollama
17k
ray-llm
90

Open issues

ollama
3.4k
ray-llm
0

Language

ollama
Go
ray-llm
-

Adopt for

ollama
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
ray-llm
-

Persona

ollama
-
ray-llm
-

Runtime

ollama
-
ray-llm
-

License

ollama
MIT license - permissive open-source licensing that allows for broad use of the tool.
ray-llm
-

Last pushed

ollama
Jul 10, 2026
ray-llm
Mar 13, 2025

Categories

ollama
LLM Frameworks, Inference & Serving
ray-llm
LLM Frameworks, Inference & Serving

Trust and health

Maintenance

ollama
Very active (96%)
ray-llm
Archived (8%)

Days since push

ollama
1d
ray-llm
485d

Archived on GitHub

ollama
No
ray-llm
Yes

Open issues (now)

ollama
3.4k
ray-llm
0

Security scan

ollama
52 low (52 low)
ray-llm
No lockfile

Full report

ollama
Trust report
ray-llm
Trust report

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

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.
GitHubDetails

Choose ray-llm if…

  • Tags unique to ray-llm: ray, llm, llm-serving.
  • Leaner open-issue backlog (0).

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.
GitHubDetails

Explore

ollama trust report →ray-llm trust report →LLM Frameworks category →Inference & Serving category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: ollama 176k · ray-llm 1.3k (synced Jul 11, 2026).

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 and ray-llm alternatives (ollama 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, 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; ray-llm trust report.