head to head · open source

Ollama vs Beam

Ollama has 181,161 GitHub stars, 17,917 forks, 3,957 open issues and last shipped yesterday. Beam has 1,780 stars, 165 forks, 21 open issues and last shipped 2 days ago. Ollama leads on adoption by 10,078% (181,161 vs 1,780 stars). Ollama is written in Go under MIT; Beam is written in Go under AGPL-3.0. Ollama has attracted 10% as many forks as stars, Beam 9%. Ollama was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (llm), so they are genuine substitutes rather than adjacent tools.

Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.

Ollama ★ 181K Beam ★ 1.8K category AI & Machine Learning

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Side by side

Ollama Beam
GitHub stars ★ 181K ★ 1.8K
License MIT AGPL-3.0
Written in Go Go
Last push 2026-09-17 2026-09-16
Forks ⑂ 18K ⑂ 165
Self-hosting Yes Yes
Data ownership Your server Your server

pick Ollama if

  • You weight community size — 181K stars and counting
  • You want the MIT license terms
  • Your stack matches Go
  • You value the larger contributor base for long-term maintenance

full Ollama profile →

pick Beam if

  • You want the Beam feature set and don't need the biggest community
  • You prefer the AGPL-3.0 license terms
  • Your stack matches Go
  • You evaluated both and Beam fits your workflow better

full Beam profile →

About Ollama

Ollama is a Go based, MIT licensed runtime that downloads and runs open source large language models such as DeepSeek, Qwen, Gemma, GLM, MiniMax and gpt oss locally on a user's own machine, and it is aimed at developers and teams that want model inference without routing prompts through a hosted API.

read the full Ollama overview →

About Beam

Beam is an open source runtime for serverless AI workloads, released under AGPL 3.0 and implemented in Go. It lives in the Python AI infrastructure ecosystem, where it gives developers a Pythonic interface for deploying and scaling GPU inference, sandboxes, and background jobs without managing infrastructure. The open source engine is Beta9, which powers the managed Beam cloud platform.

read the full Beam overview →

More in AI & Machine Learning

OpenClaw ★ 390K Hermes Agent ★ 246K Dify ★ 156K Open WebUI ★ 152K langchain ★ 147K ponytail ★ 141K

Related comparisons

ollama vs llama-cpp ollama vs vllm ollama vs gpt4all ollama vs llama-index ollama vs localai ollama vs pageindex ollama vs langfuse llama-cpp vs vllm openclaw vs hermes-agent openclaw vs open-webui openclaw vs lobechat openclaw vs anythingllm openclaw vs cherry-studio openclaw vs nanobot openclaw vs jan openclaw vs librechat dify vs langchain dify vs ponytail langchain vs ponytail dify vs graphify langchain vs graphify ponytail vs graphify dify vs claude-mem dify vs ragflow

More Machine Learning Infrastructure projects

Compare either of these against the rest of the Machine Learning Infrastructure field.

Ollama vs llama.cpp Ollama vs vllm Ollama vs GPT4All Ollama vs llama_index Ollama vs LocalAI Ollama vs PageIndex Ollama vs Langfuse Ollama vs cognee Ollama vs taipy Ollama vs dagster Ollama vs zvec Ollama vs langchain4j

Frequently asked questions

Is Ollama or Beam more popular?

Ollama has 181,161 GitHub stars and Beam has 1,780. Ollama has the larger community by that measure.

Are Ollama and Beam free?

Both are open source. Ollama is licensed under MIT and Beam under AGPL-3.0. Neither carries a licence fee.

What is the difference between Ollama and Beam?

Ollama is written in Go and Beam in Go. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.

Which should I choose, Ollama or Beam?

Choose Ollama if you want the larger community (181,161 stars) or its MIT licence terms. Choose Beam if its feature set, stack or AGPL-3.0 licence fits better. Both are self-hostable.