I am running this on 16 GB AMD Radeon 7900 GRE with 64 GB machine with ROCm and llama.cpp on Windows 11. I can use Open-webui or the native gui for the interface. It is made available via an internal IP to all members of my home.
It runs at around 26 tokens/sec and FP16, FP8 is not supported by the Radeon 7900 GRE.
I just love it.
For coding QwQ 32b is still king. But with a 16GB VRAM card it gives me ~3 tokens/sec, which is unusable.
I tried to make Gemma 3 write a powershell script with Terminal gui interface and it ran into dead-ends and finally gave up. QwQ 32B performed a lot better.
But for most general purposes it is great. My kid's been using it to feed his school textbooks and ask it questions. It is better than anything else currently.
Somehow it is more "uptight" than llama or the chinese models like Qwen. Can't put my finger on it, the Chinese models seem nicer and more talkative.
I have a 7900 GRE, which is the same except less memory. I run Gemma 3, LLama 3.1, the QwQ models and the DeepSeek distilled models using llama.cpp. They run fine, I especially like the new Gemma3-27b-Q6 (20 GB model), I get 2 tok/s on it.
I have also run Hunyuan3d-2 and generated 3d models. You would've to separate out the model generation and texture generation phase, but it works.
I run ComfyUI and bootleg gguf models. This is all on windows. Now even WSL2 works, so I am using Ubuntu-24.04 on Windows 11 to run Hunyuan3D-2.
For LLMs, llama.cpp native binaries are available. Everything just works out of the box.
I am impressed, it runs very fast. Far faster than the non-turbo version. But the primary time is being spent on the texture generation and not on the model generation. As far as I can understand this speeds up the model generation and not the texture generation. But impressive nonetheless.
I also took a head shot of my kid and ran it through https://www.adobe.com/express/feature/ai/image/remove-backgr... and cropped the image and resized it to 1024x1024 and it spit out a 3d model with texture of my kid. There are still some small artifacts, but I am impressed. It works very well with the assets/example_images. Very usable.
It runs at around 26 tokens/sec and FP16, FP8 is not supported by the Radeon 7900 GRE.
I just love it.
For coding QwQ 32b is still king. But with a 16GB VRAM card it gives me ~3 tokens/sec, which is unusable.
I tried to make Gemma 3 write a powershell script with Terminal gui interface and it ran into dead-ends and finally gave up. QwQ 32B performed a lot better.
But for most general purposes it is great. My kid's been using it to feed his school textbooks and ask it questions. It is better than anything else currently.
Somehow it is more "uptight" than llama or the chinese models like Qwen. Can't put my finger on it, the Chinese models seem nicer and more talkative.