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Dev tools · October 14, 2025

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docker/model-runner – an open-source tool for local LLMs

Hey Hacker News, We're the maintainers of docker/model-runner and wanted to share some major updates we're excited about. Link: https://github.com/docker/model-runner We are rebooting the community: https://www.docker.com/blog/rebooting-model-runner-community... At its core, model-runner is a simple, backend-agnostic tool for downloading and running local large language models. Think of it as a consistent interface to interact with different model backends. One of our main backends is llama.cpp, and we make it a point to contribute any…

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In plain words

Docker Model-Runner is an open-source tool that provides a unified interface for downloading and running large language models locally. It works with multiple model backends, including llama.cpp, and allows users to transport and share models through OCI registries like Docker Hub. Designed for developers who want to run LLMs on their own infrastructure, it simplifies model management and distribution through standardized packaging and a curated collection of pre-configured models.

written from the facts on this page · September 2026

From the sources

In the maker’s words, at launch

Hey Hacker News, We're the maintainers of docker/model-runner and wanted to share some major updates we're excited about. Link: https://github.com/docker/model-runner We are rebooting the community: https://www.docker.com/blog/rebooting-model-runner-community... At its core, model-runner is a simple, backend-agnostic tool for downloading and running local large language models. Think of it as a consistent interface to interact with different model backends. One of our main backends is llama.cpp, and we make it a point to contribute any improvements we make back upstream to their project. It also allows people to transport models via OCI registries like Docker Hub. Docker Hub hosts our curated local AI model collection, packaged as OCI Artifacts and ready to run. You can easily download, share, and upload models on Docker Hub, making it a central hub for both containerized applications and the next wave of generative AI. We've been working hard on a few things recently: - Vulkan and AMD Support: We've just merged support for Vulkan, which opens up local inference to a much wider range of GPUs, especially from AMD. - Contributor Experience: We refactored the project into a monorepo. The main goal was to make the architecture clearer and dramatically lower the barrier for new contributors to get involved and understand the codebase. - It's Fully Open Source: We know that a project from Docker might raise questions about its openness. To be clear, this is a 100% open-source, Apache 2.0 licensed project. We want to build a community around it and welcome all contributions, from documentation fixes to new model backends. - DGX Spark day-0 support, we've got it! Our goal is to grow the community. We'll be here all day to answer any questions you have. We'd love for you to check it out, give us a star if you like it, and let us know what you think. Thanks!

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