Can the RTX 3080 10 GB run Wan 2.2 I2V A14B?
Not at full quality. The 16-bit and 8-bit files are too big for the RTX 3080 10 GB; the largest that fits is Q2_K (5.3 GB).
Q2_K (5.3 GB) fits with only 0.4 GB to spare (about 9.6 GB of 10 GB). Quality: heavy loss; a last resort. For better quality, Q3_K_M (7.2 GB) also runs, with about 1.5 GB spilling into system RAM - a little slower, still practical.
Also try the FP8 file (14.3 GB) on this GPU. It does not fit entirely, but a current ComfyUI streams the overflow from RAM and native 8-bit files often beat a small GGUF that does fit. Dynamic VRAM →
Using Kijai's WanVideoWrapper instead of the native nodes? Its WanVideo BlockSwap node keeps part of the model in system RAM. To run the FP8 file (14.3 GB) on RTX 3080 10 GB, start with blocks_to_swap ≈ 26 (of 40). Each block is about 0.4 GB; raise the number if you still run out of memory, lower it for speed. estimate WanVideoWrapper →
01What to download
| Part | File | Folder | Size | |
|---|---|---|---|---|
| Model | Wan2.2-I2V-A14B-HighNoise-Q2_K.gguf high-noise model (early steps) Q2_K · QuantStack/Wan2.2-I2V-A14B-GGUF | models/unet | 5.3 GB | Download → |
| Model | Wan2.2-I2V-A14B-LowNoise-Q2_K.gguf low-noise model (late steps) Q2_K · QuantStack/Wan2.2-I2V-A14B-GGUF | models/unet | 5.3 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 | 17.6 GB | |||
Alternatives: UMT5-XXL FP16 (11.4 GB). Sizes from Hugging Face, 2026-10-01.
02Every Wan 2.2 I2V file on 10 GB
| File | Size | Needed | On this card | Quality | Download |
|---|---|---|---|---|---|
| 16-bit SAFETENSORS · Comfy-Org | 28.6 GB | 32.9 GB | 22.9 GB too big | the original weights | Hugging Face → |
| Q8_0 GGUF · QuantStack | 15.4 GB | 19.7 GB | 9.7 GB too big | practically identical to the original | Hugging Face → |
| FP8 SAFETENSORS · Comfy-Org | 14.3 GB | 18.6 GB | 8.6 GB too big | practically identical to the original | Hugging Face → |
| Q6_K GGUF · QuantStack | 12.0 GB | 16.3 GB | 6.3 GB too big | very close to the original | Hugging Face → |
| Q5_K_M GGUF · QuantStack | 10.8 GB | 15.1 GB | 5.1 GB too big | close; small differences in fine detail | Hugging Face → |
| Q4_K_M GGUF · QuantStack | 9.7 GB | 14.0 GB | 4.0 GB too big | good; some loss in fine detail and text | Hugging Face → |
| Q3_K_M GGUF · QuantStack | 7.2 GB | 11.5 GB | spills 1.5 GB | noticeable loss of detail | Hugging Face → |
| Q2_K ← GGUF · QuantStack | 5.3 GB | 9.6 GB | fits · 0.4 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 RTX 3080 10 GB, send your time per image and peak VRAM and it will appear here, credited.
04With more VRAM
With 20 GB you could run Wan 2.2 I2V at 8-bit or better (Q8_0, 15.4 GB) with no offloading.
What changes from the RTX 3080 10 GB to the RTX 3090 24 GB → · What changes from the RTX 3080 10 GB to the RTX 5070 Ti 16 GB →
05About the RTX 3080 10 GB
The RTX 3080 10 GB (Ampere) has no FP8 compute. FP8 files still load and save memory, but ComfyUI converts them back before the maths, so there is no speed gain - Q8_0 GGUF is the closer-to-original 8-bit choice. ComfyUI can compute INT8 files natively on NVIDIA, which is worth a try where a model offers one.
10 GB GDDR6X · 320-bit · 760 GB/s · Ampere. Everything that runs on it →
06Questions
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 RTX 3080 10 GB?
Q2_K (5.3 GB) from QuantStack/Wan2.2-I2V-A14B-GGUF. Load it with Unet Loader (GGUF) from the ComfyUI-GGUF node pack.
FP8 or Q8_0 for Wan 2.2 I2V on the RTX 3080 10 GB?
Q8_0 (15.4 GB). The RTX 3080 10 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 RTX 3080 10 GB?
17.6 GB: Wan2.2-I2V-A14B-HighNoise-Q2_K.gguf, Wan2.2-I2V-A14B-LowNoise-Q2_K.gguf, umt5_xxl_fp8_e4m3fn_scaled.safetensors, wan_2.1_vae.safetensors.