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OpenAI gpt-oss:20b runs on a Mac mini

The author describes how to run OpenAI’s gpt-oss:20b model locally on a Mac mini (M6) with 32 GB of RAM using Ollama, Open WebUI, and the Python API.

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Key points

  • gpt-oss:20b runs on a Mac mini with 32 GB RAM via Ollama
  • gpt-oss:20b has ~21 billion parameters and fits on 12 GB GPU memory
  • Local inference takes 16.28 s total, 260.42 tokens/s input, 38.80 tokens/s response

The gpt-oss:20b model, which has about 21 billion parameters, fits on 12 GB of GPU memory and can be run without a Docker container. The author measured a total processing time of 16.28 seconds, an input speed of 260.42 tokens/second and a response speed of 38.80 tokens/second. The model can also be accessed through a browser interface via Open WebUI, which the author installed with Docker.

The post highlights the benefits of local inference—avoiding cloud API fees, reducing data leakage risk, and allowing custom integration through Python or HTTP APIs. It also notes that the model can be combined with RAG for document‑based queries, though the author has not yet set up the Open WebUI RAG API.

The story so far

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Full story from note.com · by watabin|愛(AI)と共に · via Search: OpenAIOpen source ↗

With Love (AI): Running OpenAI's AI models on a Mac mini!

note.com · 20 October 2026

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This text was published by note.com and written by watabin|愛(AI)と共に. It is reproduced here with attribution so you can read it in full; the rights remain with the publisher. Read it at the source ↗

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The headline, key points and digest above were generated by Digest AI's editorial model from the linked sources. Automated summaries can contain errors: the sources are the record. Spotted a mistake? Tell us. Published by Martin K., who runs Digest AI and handles corrections.

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