Assuming you’re using ollama (is there another reason to use ollama.com?), you can use compatible files from huggingface directly in ollama. The model page will give you the instructions for the command to run; I always change ollama run to ollama pull , though. Instructions: https://huggingface.co/docs/hub/ollama

You should be able to fit Qwen3 32B at Q4_K_M with an acceptable context, and it did very well on math benchmarks (with thinking enabled). You can disable thinking by including /no_think at the end of your prompt to speed up responses, but I’m not sure how well it handles math under those circumstances. I wouldn’t even consider disabling thinking unless you were grading one question per prompt.

The ollama Qwen3 page is https://ollama.com/library/qwen3:32b and the default 32B quant is Q4_K_M. I personally am using the Q6_K quant by unsloth, and their quants have been great (when supported by ollama), often being the first to fix bugs impacting other quantizations.

I’m not sure if Q4_K_M is the optimal quant style for Intel Arc, but the others that might be better are not supported by ollama, anyway, as far as I know.

Qwen3’s real world knowledge is bad, so if there are questions that rely on that you may need to include the relevant facts as part of the prompt or use an ollama frontend that supports web searches.

Other options: This does seem like something Gemma3 27B would be good at, so it’s too bad you can’t use it. Older Gemmas may be good, but I’m not sure. Llama3.3 70B is also out, unless you have a decent amount of system RAM and are okay with offloading less than half to GPU. I could see it outperforming my recommendation below but I would be very surprised for the 8B version to outperform it. Older Qwen2.5 is decent at math but unless you grab QwQ doesn’t include thinking.