How to Run DeepSeek R1 Distilled Reasoning Models on RyzenAI and Radeon GPUs

I have a Radeon 7900 XTX 24GB and have been using the deepseek-r1:14b for a couple days. It achieves about 45 tokens/s. Only after reading this article did I realize that the 32B model would also fit entirely (23GB used). And since Ollama [0] was already installed, it as as easy as running: ollama run deepseek-r1:32b

The 32B model achieves about 25 tokens/s, which is faster than I can read. However, the "thinking" time is mostly a lower quality overhead taking ~1-4 minutes before the Solution/Answer

You can view the model performance within ollama using the command: /set verbose

[0] https://github.com/ollama/ollama

I wrote a similar post about a week ago, but for an [unsupported] Radeon RX 5500 with 4Gi RAM with ollama and fedora 41. Can only run llama:3.2 or deepseek-r1:1.5b, but they're pretty usable if you're ok with a small model and it's for personal use.

I didn't go into detail about how to setup openweb-ui, but there is documentation for the on the project's site.

https://blue42.net/linux-ollama-radeon-rx5500/post/

Has anyone seen an in-depth comparison between radeon 7900 xtx vs 3090 rtx specific to R1?

Ok, but how many tokens/sec will run a 70B model on AMD 395+ ?

As an aside, either the latest Linux or 6.14 has/will have support for Ryzen XDNA AI chips on their mobile APUs.

Might not be appropriate for this model, but it could be for small models.

There are also Vulkan backends included in most all-in-one LLM runners for a while; can be useful for cards not supported by ROCm.

in my case with a 6900xt:

1. sudo pacman -S ollama-rocm

2. ollama serve

3. ollama run deepseek-r1:32b