Home/Compare/beta9 vs ollama

Comparison

beta9 vs ollama

Verdict

Pick beta9 when license: beta9 is AGPL-3.0, ollama is MIT; pick ollama when license: ollama is MIT, beta9 is AGPL-3.0.

Markdown twin · beta9 alternatives · ollama alternatives

GraphCanon updated today

beta9 logo

beta9

beam-cloud/beta9

1.7kpushed Jul 10, 2026
vs
ollama logo

ollama

ollama/ollama

176kpushed Jul 10, 2026

Trust & integrity

Signalbeta9ollama
Maintenance
Very active (0d since push)
As of today · github_public_v1
Very active (1d 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)
No lockfile
As of today · none
52 low (52 low)
As of today · osv@v1

Tagline

beta9
Ultrafast serverless GPU inference, sandboxes, and background jobs
ollama
Get up and running with various large language models using Ollama.

Stars

beta9
1.7k
ollama
176k

Forks

beta9
145
ollama
17k

Open issues

beta9
14
ollama
3.4k

Language

beta9
Go
ollama
Go

Adopt for

beta9
-
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

Persona

beta9
-
ollama
-

Runtime

beta9
-
ollama
-

License

beta9
AGPL-3.0
ollama
MIT license - permissive open-source licensing that allows for broad use of the tool.

Last pushed

beta9
Jul 10, 2026
ollama
Jul 10, 2026

Categories

beta9
LLM Frameworks, Inference & Serving, Developer Tools
ollama
LLM Frameworks, Inference & Serving

Trust and health

Days since push

beta9
0d
ollama
1d

Open issues (now)

beta9
14
ollama
3.4k

Security scan

beta9
No lockfile
ollama
52 low (52 low)

Full report

Choose beta9 if…

  • License: beta9 is AGPL-3.0, ollama is MIT.
  • Tags unique to beta9: fine-tuning, faas, functions-as-a-service, cloudrun.
  • Also covers Developer Tools.

When NOT to use beta9

  • 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.
  • Developer Tools: A gateway is overkill when you're pinned to a single provider and model.

Choose ollama if…

  • License: ollama is MIT, beta9 is AGPL-3.0.
  • 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.

Explore

Sources

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

GitHub stars on cards: beta9 1.7k · ollama 176k (synced Jul 11, 2026).

Common questions

What is the difference between beta9 and ollama?
beta9: Ultrafast serverless GPU inference, sandboxes, and background jobs. ollama: Get up and running with various large language models using Ollama.. See the comparison table for live GitHub stats and shared categories.
When should I choose beta9 over ollama?
Choose beta9 over ollama when License: beta9 is AGPL-3.0, ollama is MIT; Tags unique to beta9: fine-tuning, faas, functions-as-a-service, cloudrun; Also covers Developer Tools.
When should I choose ollama over beta9?
Choose ollama over beta9 when License: ollama is MIT, beta9 is AGPL-3.0; 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 avoid beta9?
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. Developer Tools: A gateway is overkill when you're pinned to a single provider and model.
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.
Is beta9 or ollama more popular on GitHub?
ollama has more GitHub stars (175,936 vs 1,696). Stars measure visibility, not whether either tool fits your constraints.
Are beta9 and ollama open source?
Yes - both are open-source projects on GitHub (beta9: AGPL-3.0, ollama: MIT).
Where can I find alternatives to beta9 or ollama?
GraphCanon lists graph-backed alternatives at beta9 alternatives and ollama alternatives (beta9 markdown twin, ollama 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, beta9 or ollama?
beta9: Very active. ollama: Very active. 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 beta9 and ollama?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: beta9 trust report; ollama trust report.