Can the Radeon 8060S (Strix Halo) 96 GB run Wan 2.2 T2V A14B?
Yes. 16-bit fits on the Radeon 8060S (Strix Halo) 96 GB with 63.1 GB to spare.
16-bit (28.6 GB) needs about 32.9 GB in use, so 63.1 GB of the 96 GB stays free: room for a larger image, a LoRA or a ControlNet.
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | wan2.2_t2v_high_noise_14B_fp16.safetensors high-noise model (early steps) 16-bit · Comfy-Org/Wan_2.2_ComfyUI_Repackaged | models/diffusion_models | 28.6 GB | Download → |
| Model | wan2.2_t2v_low_noise_14B_fp16.safetensors low-noise model (late steps) 16-bit · Comfy-Org/Wan_2.2_ComfyUI_Repackaged | models/diffusion_models | 28.6 GB | Download → |
| Text encoder | umt5_xxl_fp8_e4m3fn_scaled.safetensors UMT5-XXL FP8 (scaled) · Comfy-Org/Wan_2.1_ComfyUI_repackaged | models/text_encoders | 6.7 GB | Download → |
| VAE | wan_2.1_vae.safetensors Wan 2.1 VAE · Comfy-Org/Wan_2.2_ComfyUI_Repackaged | models/vae | 0.3 GB | Download → |
| Total download · keep about the same free on disk | 64.1 GB | |||
Alternatives: UMT5-XXL FP16 (11.4 GB). Sizes from Hugging Face, 2026-10-01.
Free ComfyUI workflow, tested on my RTX 5060 Ti: FP8 workflow (.json) · GGUF Q5_K_M workflow (.json). Drag the file into ComfyUI. All workflows →
Shared memory: about 70.1 GB of your 128 GB. On this machine the model, the text encoder, the VAE and the operating system all use the same memory. That leaves room, so nothing has to be swapped to disk. calculated
02Every Wan 2.2 T2V file on 96 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit ← SAFETENSORS · Comfy-Org | 28.6 GB | 32.9 GB | fits · 63.1 GB spare | the original weights | Hugging Face → |
| Q8_0 GGUF · QuantStack | 15.4 GB | 19.7 GB | fits · 76.3 GB spare | practically identical to the original | Hugging Face → |
| FP8 SAFETENSORS · Comfy-Org | 14.3 GB | 18.6 GB | fits · 77.4 GB spare | practically identical to the original | Hugging Face → |
| Q6_K GGUF · QuantStack | 12.0 GB | 16.3 GB | fits · 79.7 GB spare | very close to the original | Hugging Face → |
| Q5_K_M GGUF · QuantStack | 10.8 GB | 15.1 GB | fits · 80.9 GB spare | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · QuantStack | 9.7 GB | 14.0 GB | fits · 82.0 GB spare | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · QuantStack | 7.2 GB | 11.5 GB | fits · 84.5 GB spare | noticeable loss of detail | Hugging Face → |
| Q2_K GGUF · QuantStack | 5.3 GB | 9.6 GB | fits · 86.4 GB spare | heavy loss; a last resort | Hugging Face → |
“Needed” adds 3.5 GB of working memory for Wan 2.2 T2V and a 0.8 GB reserve. Sizes 2026-10-01. Wan 2.2 A14B uses two files of this size (high-noise and low-noise); only one sits in VRAM at a time, both must fit in system RAM.
03Measured and reported results
| Label | Setup | Result | Peak VRAM | Date | Source |
|---|---|---|---|---|---|
| reported | Wan 2.2 T2V A14B (high+low noise experts) · 640x640 · 4 steps “Steady state | 197 s/it | 186 s/it | 26 min 51 s” AMD ROCm blog, Ryzen AI Max+ 395; s/it for high-noise / low-noise expert; 26 min 51 s = 1611 s; first run 36 min 14 s; vendor-published | 1611 s / clip (81 frames) | — | 2026-07-14 | rocm.blogs.amd.com → |
Other people's numbers are copied as published, with a link. Send yours.
04About the Radeon 8060S (Strix Halo) 96 GB
This is an integrated GPU that uses system memory. AMD states that up to 96 GB of the 128 GB can be set aside as graphics memory on Windows, which is why it can hold models no consumer graphics card can. The catch is speed: the GPU itself (40 compute units) is far smaller than a big desktop card, and its memory bandwidth is a fraction of one, so each step takes much longer. Treat the verdicts here as 'it fits', not 'it is fast'.
96 GB LPDDR5X (shared system memory) · 256-bit · 256 GB/s · RDNA 3.5. Everything that runs on it →
05Questions
How much VRAM does Wan 2.2 T2V need?
Around 9.6 GB with the smallest file (Q2_K) and 18.6 GB with an 8-bit file (FP8). The full 16-bit file needs about 32.9 GB.
Which Wan 2.2 T2V file should I download for the Radeon 8060S (Strix Halo) 96 GB?
16-bit (28.6 GB) from Comfy-Org/Wan_2.2_ComfyUI_Repackaged.
FP8 or Q8_0 for Wan 2.2 T2V on the Radeon 8060S (Strix Halo) 96 GB?
Q8_0 (15.4 GB). The Radeon 8060S (Strix Halo) 96 GB has no FP8 maths, so FP8 (14.3 GB) only saves memory and is a step further from the original.
How much do I need to download for Wan 2.2 T2V on the Radeon 8060S (Strix Halo) 96 GB?
64.1 GB: wan2.2_t2v_high_noise_14B_fp16.safetensors, wan2.2_t2v_low_noise_14B_fp16.safetensors, umt5_xxl_fp8_e4m3fn_scaled.safetensors, wan_2.1_vae.safetensors.