I finally got MiniMax H3 working really well on AMD, including multi-GPU, so I thought I'd share a few things that saved me a lot of trial and error.

For reference, my setup is 2x AMD Radeon RX 7900 XTX, 24 GB VRAM each. Some settings below, especially the multi-GPU VRAM allocation, are specific to my hardware.

I also uploaded the workflow + notes on Civitai here:

https://civitai.com/models/2857584/minimax-h3-amd-hip-and-multigpu-tips?modelVersionId=3227624

ComfyUI ROCm build

I'm using the build from patientx-cfz:

https://github.com/patientx-cfz/comfyui-rocm

It works extremely well for me and has been stable/error-free. Just follow the installation instructions on GitHub.

After installing, make sure to update everything using the included batch files:

comfyui-rocm-updater.bat
rocm-pytorch-package-updater.bat

Then edit comfyui-rocm.bat, find:

set PARAMS=

and add:

--use-sage-attention

at the end.

MiniMax H3 models

I recommend using the Q8_0 GGUF models.

The INT8 versions also work and are roughly as fast as Q8, but in my testing they require a lot more VRAM with no noticeable quality benefit.

I'm using the Unsloth versions:

https://huggingface.co/unsloth/MiniMax-H3-GGUF/tree/main

Specifically:

minimax_h3_fl2va_pruned-Q8_0.gguf
minimax_h3_ref2va_pruned-Q8_0.gguf

If you only have one 24 GB GPU, I'd suggest starting with Q5_0 instead. If you have 32GB maybe try Q6 or Q8.

Important: NVFP4 CLIP works on AMD

Download the recommended CLIP:

qwen3vl_32b_minimax_h3_nvfp4_awq

This was probably the biggest source of confusion for me.

I'm familiar with NVFP4 from the LLM world, so because it's associated with NVIDIA hardware I automatically assumed it wouldn't work on AMD.

I tried several GGUF CLIP models and only managed to make them work properly for T2V. For the other workflows, no luck.

Turns out that assumption was wrong:

You do NOT need a GGUF CLIP. The recommended NVFP4 model works on AMD in this setup, the included comfy-kitchen module handles it transparently.

Multi-GPU

Install these two custom nodes through ComfyUI Manager:

comfyui-multigpu
ComfyUI-GGUF

After installing comfyui-multigpu, use:

UnetLoaderGGUFDisTorch2MultiGpu

as the GGUF loader.

On my 2x 7900 XTX 24 GB setup, I use:

virtual_vram_gb = 20

20 GB is specific to my setup, so don't blindly copy that value if your GPUs have a different amount of VRAM... With my two 7900 XTXs, the second GPU essentially works as a very fast cache/offload device for the primary GPU doing the computation. The 20 means 20Gb of the second card are used as cache for the first card.

Turbo LoRAs

You can of course add LoRAs on top. The H3 LoRA ecosystem is moving quickly, but these were among the first Turbo LoRAs:

https://huggingface.co/lightx2v/Minimax-h3-Turbo/tree/main

They let you use around 4 or 8 steps instead of the default 20, depending on the LoRA/workflow. Actually the 4 step works best with 5/6 steps, soemtimes 4 steps is a bit rough on fast movements.

Again, I've uploaded the workflow I'm using here:

https://civitai.com/models/2857584/minimax-h3-amd-hip-and-multigpu-tips?modelVersionId=3227624

Hopefully this saves some AMD users a few hours of experimenting. :)

times: the workflow linked above took 2min 13sec for 4 steps, it's a 5 second video 0.4 megapixels. Also I NEVER got an OOM this has been extremely reliable for me.