FramePack I2V (HunyuanVideo 13B) on NVIDIA GeForce RTX 4070 SUPER

Can the NVIDIA GeForce RTX 4070 SUPER run FramePack I2V (HunyuanVideo 13B)?

64 pts

Yes, with little memory to spare

Tight fit. At FP8 it needs about 10.8 GB of 12.0 GB usable, with an estimated speed of 14.7 min.

Best precision: FP8
Memory mode: Sequential CPU offload
Time per clip: 14.7 min
Output: 640×640, 150 frames, 25 steps

Download FramePack I2V (HunyuanVideo 13B)

Original weights · Hugging Face

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

huggingface.co/lllyasviel/FramePackI2V_HY (opens in a new tab)

No sign-in needed.

Official repo · GitHub

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

github.com/lllyasviel/FramePack (opens in a new tab)

git clone https://github.com/lllyasviel/FramePack

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

How the B 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.	32.6 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	10.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	6.8 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.	15.0 / 15
Total	64.4 / 100	64 ptsGood (B) · 64 of 100 points: Model quality 32.6/45, Memory fit 10.0/25, Speed 6.8/15, Memory use 15.0/15

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

Every precision on the NVIDIA GeForce RTX 4070 SUPER

Precision	Memory needed	Available	Time per output	Memory mode	Fit	Grade · points	Download
`FP16`	15.3 GB	12.0 GB	—	—	Won't run	9 ptsWon't run (F) · 9 of 100 points: Model quality 10.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	Original weights (opens in a new tab)
`FP8`	10.8 GB	12.0 GB	14.7 min	Sequential CPU offload	Tight fit	64 ptsGood (B) · 64 of 100 points: Model quality 32.6/45, Memory fit 10.0/25, Speed 6.8/15, Memory use 15.0/15	Original weights (opens in a new tab)

Other hardware that runs it

82 ptsGreat (A) · 82 of 100 points: Model quality 32.6/45, Memory fit 23.0/25, Speed 11.6/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 FP8 · 5.0 min
81 ptsGreat (A) · 81 of 100 points: Model quality 33.3/45, Memory fit 25.0/25, Speed 11.8/15, Memory use 11.9/15 NVIDIA RTX PRO 6000 Blackwell FP16 · 4.9 min
77 ptsGreat (A) · 77 of 100 points: Model quality 32.6/45, Memory fit 20.0/25, Speed 10.4/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 FP8 · 6.3 min
77 ptsGreat (A) · 77 of 100 points: Model quality 33.3/45, Memory fit 25.0/25, Speed 7.3/15, Memory use 11.9/15 AMD Ryzen AI Max+ 395 (128 GB) FP16 · 12.8 min
77 ptsGreat (A) · 77 of 100 points: Model quality 32.6/45, Memory fit 20.0/25, Speed 9.8/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX FP8 · 7.0 min
76 ptsGreat (A) · 76 of 100 points: Model quality 32.6/45, Memory fit 25.0/25, Speed 3.4/15, Memory use 15.0/15 Apple M4 Pro (48 GB) FP8 · 59.1 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.