head to head · open source
Ollama vs Laminar
Ollama has 181,161 GitHub stars, 17,917 forks, 3,957 open issues and last shipped yesterday. Laminar has 3,265 stars, 239 forks, 116 open issues and last shipped yesterday. Ollama leads on adoption by 5,449% (181,161 vs 3,265 stars). Ollama is written in Go under MIT; Laminar is written in TypeScript under Apache-2.0. Ollama has attracted 10% as many forks as stars, Laminar 7%. Ollama was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| Ollama | Laminar | |
|---|---|---|
| GitHub stars | ★ 181K | ★ 3.3K |
| License | MIT | Apache-2.0 |
| Written in | Go | TypeScript |
| Last push | 2026-09-17 | 2026-09-17 |
| Forks | ⑂ 18K | ⑂ 239 |
| 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
pick Laminar if
- You want the Laminar feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches TypeScript
- You evaluated both and Laminar fits your workflow better
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 Laminar
Laminar is an open source observability platform purpose built for AI agents, distributed under the Apache 2.0 license and written primarily in TypeScript. It was built by the team behind Y Combinator's S24 batch and lives in the AI and machine learning infrastructure ecosystem, with a topic list spanning agent observability, LLM evaluation, LLMOps and AIOps. The project ships as a tracing and evaluation stack rather than a general purpose APM tool, and its homepage at laminar.sh hosts both documentation and a managed offering.
read the full Laminar overview →
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Frequently asked questions
Is Ollama or Laminar more popular?
Ollama has 181,161 GitHub stars and Laminar has 3,265. Ollama has the larger community by that measure.
Are Ollama and Laminar free?
Both are open source. Ollama is licensed under MIT and Laminar under Apache-2.0. Neither carries a licence fee.
What is the difference between Ollama and Laminar?
Ollama is written in Go and Laminar in TypeScript. 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 Laminar?
Choose Ollama if you want the larger community (181,161 stars) or its MIT licence terms. Choose Laminar if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.