HunyuanImage-3.0 Release

[thaivb]

Feature Idea

This is url.... https://huggingface.co/tencent/HunyuanImage-3.0

Existing Solutions

No response

Other

No response

[kabachuha]

We need MultiGPU, desperately

[nitinh12]

@comfyanonymous will you support this model? It would be great to see how you will handle it.

[comfyui-wiki]

I would say, even if it's supported in ComfyUI, it will still be very hard for most users to run it locally.

80B and 170GB, OMG

[kabachuha]

Technically, it's an autoregressive LLM (next token prediction)* and it's a MoE (mixture of experts), meaning you can keep all attention in VRAM and offload as few experts as you can to CPU. The bottleneck becomes RAM size and VRAM-RAM communication and it's not very bad, for example, at 5090 which supports PCI.E-5 x16.

If one has multigpu, it's even better. People launch dense models like LLaMA 3.3 70b on their 24x2 GB VRAM setups just fine at 4 bit quantization. In lack of an RTX 6000 PRO 96GBs, LocalLLaMA people have MultiGPU setups like 4x3090, and it's quite doable if you have collected GPUs since the start of the AI craze some years ago.

A large share of ComfyUI consumer users can launch 80b models (especially when they are MoEs), all we need is MultiGPU support

• They updated the page prediction, and it's in fact a BAGEL-like AutoregressiveLLM-Diffusion generation single model hybrid, making it even faster for image generation!

[wsbagnsv1]

Yeah with ggufs (i will try to quant, i dont know how yet but i will get it to work 😅) this is 100% possible to run with cpu offload (with 64gb ram) even on a single gpu, but the more gpus and the more vram the better (;

[zwukong]

they will publish a small distill size later,no need to hurry

[comfyanonymous]

This looks like a model that people are going to try once, wait more than 10 minutes for a 1MP image and then never use again so it's probably not worth implementing.

[kabachuha]

@zwukong Having the bigger model is still better, distills usually destroy image quality and especially prompt following

[kabachuha]

@comfyanonymous Have you tried it in cloud?

[kabachuha]

Anyway, seems like we need quants in any case. Hopefully, people like LLaMA cpp or Nunchaku will do fp4. (Then it will be a external wrapper)

[zwukong]

haha, so big

[Ulexer]

This looks like a model that people are going to try once, wait more than 10 minutes for a 1MP image and then never use again so it's probably not worth implementing.

Being a 13B active MoE, shouldn't it be as fast as Flux with CFG?

[Jongulo]

This looks like a model that people are going to try once, wait more than 10 minutes for a 1MP image and then never use again so it's probably not worth implementing.

You raised 17 million fucking dollars and can't be assed to actually use the money to support the latest oss models?

[souki202]

The Qwen-image model still seems to maintain reasonably high quality even when quantized to Q3.

I speculate that even a large 80B model, if it has strong performance and the environment is set up with proper optimization and acceleration LoRAs, could achieve generation within a realistic timeframe, given sufficient RAM and 32GB or 24GB+ VRAM. Hopefully.