Can the Radeon 8060S (Strix Halo) 96 GB run Wan 2.2 I2V 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_i2v_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_i2v_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.
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 I2V 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 I2V 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
Nobody has sent measured numbers for this pair yet. If you run Wan 2.2 I2V on a Radeon 8060S (Strix Halo) 96 GB, send your time per image and peak VRAM and it will appear here, credited.
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 I2V 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 I2V 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 I2V 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 I2V on the Radeon 8060S (Strix Halo) 96 GB?
64.1 GB: wan2.2_i2v_high_noise_14B_fp16.safetensors, wan2.2_i2v_low_noise_14B_fp16.safetensors, umt5_xxl_fp8_e4m3fn_scaled.safetensors, wan_2.1_vae.safetensors.