Docker Model Runner does everything Ollama does, but I’m still not switching
I have been using Ollama to run local LLMs for the longest time now, and I don’t have a lot to complain about. It gets the job done, and I don’t have to tweak a lot of things. Recently, Docker announced its own model runner, which offers many of the same features you get with Ollama. It can pull, run, manage, and serve local AI models through Docker Desktop or Docker Engine. It supports GGUF models through llama.cpp, Safetensors models through vLLM, hardware acceleration on supported systems, and models from Docker Hub, Hugging Face, or other OCI registries. I have been using it instead of Ollama for almost a week now, but I can’t say I am sticking to it.
I have been using Ollama to run local LLMs for the longest time now, and I don’t have a lot to complain about. It gets the job done, and I don’t have to tweak a lot of things. Recently, Docker announced its own model runner, which offers many of the same features you get with Ollama. It can pull, run, manage, and serve local AI models through Docker Desktop or Docker Engine. It supports GGUF models through llama.cpp, Safetensors models through vLLM, hardware acceleration on supported systems, and models from Docker Hub, Hugging Face, or other OCI registries. I have been using it instead of Ollama for almost a week now, but I can’t say I am sticking to it.
Christoffer Olsen
Denmark
Denmark
Published by: aplhsindia.in
