FWIW, Ollama already does most of this:
- Cross-platform
- Sets up a local API server
The tradeoff is a somewhat higher learning curve, since you need to manually browse the model library and choose the model/quantization that best fit your workflow and hardware. OTOH, it's also open-source unlike LMStudio which is proprietary.
Re:A Guide to Local Coding Models
by randallsquared on Sunday December 21, 2025 @05:50PM
(#46349425)
I assumed from the name that it only ran llama-derived models, rather than whatever is available at huggingface. Is that not the case?
No, they have quite a broad list of models: https://ollama.com/search
[edit] Oh and apparently you can also directly run some models directly from HuggingFace: https://huggingface.co/docs/hub/ollama
Re:A Guide to Local Coding Models
by ashirviskas on Monday December 22, 2025 @09:30PM
(#46361752)
Just use llama.cpp. Ollama tried to force their custom API (not the openai standard), they obscure the downloaded models making them a pain to use with other implementations, blatantly used llama.cpp as a thin wrapper without communicating it properly and now has to differentiate somehow to start making money.
If you've ever used a terminal, use llama.cpp. You can also directly run models from llama.cpp afaik.
Yes, I wanted to try it already but setting up an environment with an MI50 was a bit tricky so I wanted to try something I knew first. Now that I have ollama running I will give llama.cpp a shot.
Re:A Guide to Local Coding Models
by ashirviskas on Tuesday December 23, 2025 @09:15AM
(#46365469)
Ooh, I have experience with it. If you're on linux, just use Vulkan. If you face any other issues, just google my username + "MI50 32GB vbios reddit". It depends on which vBIOS you have, but that post on reddit has most of the info you may need. Good luck!
It's cross-platform (Win/Mac/Linux), detects the most appropriate GPU in your system and tells you whether the model you want to download will run within it's RAM footprint.
It lets you set up a local server that you can access through API calls as if you were remotely connected to an online service.