I’ve just re-discovered ollama and it’s come on a long way and has reduced the very difficult task of locally hosting your own LLM (and getting it running on a GPU) to simply installing a deb! It also works for Windows and Mac, so can help everyone.
I’d like to see Lemmy become useful for specific technical sub branches instead of trying to find the best existing community which can be subjective making information difficult to find, so I created !Ollama@lemmy.world for everyone to discuss, ask questions, and help each other out with ollama!
So, please, join, subscribe and feel free to post, ask questions, post tips / projects, and help out where you can!
Thanks!
Actually, to go ahead and answer, the “fastest” path would be LM Studio (which supports MLX quants natively and is not time intensive to install), and a DWQ quantization (which is a newer, higher quality variant of MLX models).
Hopefully one of these models, depending on how much RAM you have:
https://huggingface.co/mlx-community/Qwen3-14B-4bit-DWQ-053125
https://huggingface.co/mlx-community/Magistral-Small-2506-4bit-DWQ
https://huggingface.co/mlx-community/Qwen3-30B-A3B-4bit-DWQ-0508
https://huggingface.co/mlx-community/GLM-4-32B-0414-4bit-DWQ
With a bit more time invested, you could try to set up Open Web UI as an alterantive interface (which has its own built in web search like Gemini): https://openwebui.com/
And then use LM Studio (or some other MLX backend, or even free online API models) as the ‘engine’
Alternatively, especially if you have a small RAM pool, Gemma 12B QAT Q4_0 is quite good, and you can run it with LM Studio or anything else that supports a GGUF. Not sure about 12B-ish thinking models off the top of my head, I’d have to look around.
This is all new to me, so I’ll have to do a bit of homework on this. Thanks for the detailed and linked reply!
I was a bit mistaken, these are the models you should consider:
https://huggingface.co/mlx-community/Qwen3-4B-4bit-DWQ
https://huggingface.co/AnteriorAI/gemma-3-4b-it-qat-q4_0-gguf
https://huggingface.co/unsloth/Jan-nano-GGUF (specifically the UD-Q4 or UD-Q5 file)
they are state-of-the-art at this size, as far as I know.
Awesome, I’ll give these a spin and see how it goes. Much appreciated!