Feature Request: Enhance Wan 2.2 Video Model Support on Intel Arc B580 (PyTorch XPU Backend) – Urgen

[hello-iamtekin]

Dear Intel AI Frameworks / PyTorch XPU Team,

I hope this email finds you well.

I am an enthusiastic user of Intel Arc B580 GPU (Battlemage series, 12GB GDDR6) running on Windows, and I am very excited about the native PyTorch XPU support introduced in PyTorch 2.5+ (and further improvements in 2.7+). Image generation models (e.g., SDXL, Flux) run excellently with great performance on my Arc B580 using ComfyUI + --device xpu.

However, there is a significant gap in support for popular video generation models, specifically Wan 2.2 (Wan 2.1/2.2 T2V/I2V, 5B/14B variants) when used via ComfyUI + Kijai WanVideoWrapper (the most common community wrapper).

Current issues observed on Arc B580 (XPU backend):

• fp64 operations not supported → Many Wan sampler nodes require fp64, leading to fallback to CPU or crashes.
• "non-uniform work-groups" or kernel compilation errors during T5 text encoder or WanVideoSampler execution.
• Quantized models (fp8/quanto int8) partially work but result in low quality or OOM at higher resolutions (e.g., 960x544+).
• Partial successes reported (e.g., 640x352 @ 60s generation time in some Docker/ComfyUI tests), but inconsistent and far from NVIDIA-level stability.
• Related open issues:
  • //github.com/kijai/ComfyUI-WanVideoWrapper/issues/711 (fp64 on Intel Arc)
  • //github.com/intel/AI-Playground/issues/355 (Wan 2.2 fails on B580 in AI Playground/ComfyUI backend)
  • //github.com/Comfy-Org/ComfyUI/discussions/476 (Intel Arc thread, ongoing Wan requests)
  • //github.com/Comfy-Org/ComfyUI/issues/12476(Workflow aborts on XPU during model load)

These problems force users like me to fallback to CPU mode (very slow: 20-60+ minutes per short video) or avoid Wan 2.2 entirely, despite the model's excellent quality and community popularity.

Feature request / development suggestion (urgent):

• Add better upstream support in PyTorch XPU for Wan-specific custom ops and samplers (e.g., fp64 fallback to fp16/bf16 emulation, optimized work-group handling for XMX engines).
• Improve quantized model compatibility (fp8/bf16) for video diffusion pipelines.
• Official guidance or example workflow for Wan 2.2 on Arc GPUs in ComfyUI / Diffusers.
• This would greatly boost adoption of Arc GPUs in the AI PC space, especially for local video generation (HunyuanVideo, Open-Sora gibi alternatiflerde de benzer iyileştirmeler faydalı olur).

I (and many in r/IntelArc, r/comfyui communities) would be happy to provide detailed logs, repro steps, or test patches if needed. My setup: Windows 11/Arc B580 latest drivers, PyTorch 2.7.1+xpu or latest nightly, ComfyUI latest.

Thank you for your continued excellent work on bringing PyTorch XPU to Arc GPUs. Looking forward to improved Wan 2.2 support to make Arc the go-to choice for affordable AI video creation!

[JeanetteC_Intel]

Hi hello-iamtekin,

Thank you for posting in Intel Communities.

I notice you've also submitted this same issue through our web portal, where our specialist has already responded. To avoid duplication, please let me know which support channel you'd prefer to continue with, and we'll proceed accordingly.

Looking forward to your reply.

Best regards,

JeanetteC.

Intel Customer Support Technician

[hello-iamtekin]

Let's continue with the special ticket! I only shared this for everyone to be interested in and discuss.

[JeanetteC_Intel]

Hello hello-iamtekin,

I appreciate your confirmation. Please continue working on this "feature request/development suggestion" through your existing web portal case, where our specialist will provide ongoing support and guidance.

I'll now close this discussion thread. If you require assistance in the future, please submit a new inquiry, as this thread will no longer be actively monitored.

Thank you for your understanding.

Sincerely,

JeanetteC.

Intel Customer Support Technician