Wan 2.1 I2V 14B 480P on NVIDIA RTX PRO 6000 Blackwell

Can the NVIDIA RTX PRO 6000 Blackwell run Wan 2.1 I2V 14B 480P?

77 pts

Yes, it runs well

Runs well. At FP16 it needs about 46.5 GB of 96.0 GB usable, with an estimated speed of 11.0 min.

Best precision: FP16
Memory mode: Everything on GPU
Time per clip: 11.0 min
Output: 832×480, 81 frames, 50 steps

Download Wan 2.1 I2V 14B 480P

Quantized files · GGUF for ComfyUI

Smaller GGUF versions for ComfyUI (with the ComfyUI-GGUF node). No sign-in needed; the model’s license still applies.

huggingface.co/city96/Wan2.1-I2V-14B-480P-gguf (opens in a new tab)

Original weights · Hugging Face

Full-precision files from Alibaba, for fine-tuning, vLLM, Transformers, Diffusers or ComfyUI.

huggingface.co/Wan-AI/Wan2.1-I2V-14B-480P (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Alibaba. The weights themselves download from Hugging Face.

github.com/Wan-Video/Wan2.1 (opens in a new tab)

git clone https://github.com/Wan-Video/Wan2.1

Links checked 5 days ago against Hugging Face, Ollama and GitHub.

How the A grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.	33.3 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	7.8 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	11.2 / 15
Total	77.3 / 100	77 ptsGreat (A) · 77 of 100 points: Model quality 33.3/45, Memory fit 25.0/25, Speed 7.8/15, Memory use 11.2/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every precision on the NVIDIA RTX PRO 6000 Blackwell

Precision	Memory needed	Available	Time per output	Memory mode	Fit	Grade · points	Download
`FP16`	46.5 GB	96.0 GB	11.0 min	Everything on GPU	Runs well	77 ptsGreat (A) · 77 of 100 points: Model quality 33.3/45, Memory fit 25.0/25, Speed 7.8/15, Memory use 11.2/15	Original weights (opens in a new tab)
`FP8`	26.2 GB	96.0 GB	9.9 min	Everything on GPU	Runs well	72 ptsGreat (A) · 72 of 100 points: Model quality 32.6/45, Memory fit 25.0/25, Speed 8.3/15, Memory use 6.3/15	Original weights (opens in a new tab)
`Q8 GGUF`	27.2 GB	96.0 GB	12.6 min	Everything on GPU	Runs well	71 ptsGood (B) · 71 of 100 points: Model quality 33.0/45, Memory fit 25.0/25, Speed 7.3/15, Memory use 6.5/15	GGUF (opens in a new tab)
`Q4 GGUF`	20.6 GB	96.0 GB	13.2 min	Everything on GPU	Runs well	68 ptsGood (B) · 68 of 100 points: Model quality 31.0/45, Memory fit 25.0/25, Speed 7.2/15, Memory use 4.9/15	GGUF (opens in a new tab)

Other hardware that runs it

80 ptsGreat (A) · 80 of 100 points: Model quality 32.6/45, Memory fit 25.0/25, Speed 7.7/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 FP8 · 11.3 min
75 ptsGreat (A) · 75 of 100 points: Model quality 31.0/45, Memory fit 23.0/25, Speed 6.1/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 Q4 GGUF · 18.0 min
74 ptsGreat (A) · 74 of 100 points: Model quality 33.0/45, Memory fit 25.0/25, Speed 2.0/15, Memory use 15.0/15 Apple M4 Pro (48 GB) Q8 GGUF · 2.8 h
74 ptsGreat (A) · 74 of 100 points: Model quality 31.0/45, Memory fit 23.0/25, Speed 5.8/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX Q4 GGUF · 20.1 min
74 ptsGreat (A) · 74 of 100 points: Model quality 33.3/45, Memory fit 25.0/25, Speed 4.8/15, Memory use 11.2/15 AMD Ryzen AI Max+ 395 (128 GB) FP16 · 28.8 min

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.