HunyuanVideo 13B on AMD EPYC 7002 / 7003 series NAS (64 GB)

Can the AMD EPYC 7002 / 7003 series NAS (64 GB) run HunyuanVideo 13B?

Barely: it runs very slowly

Very slow. At Q8 GGUF it needs about 44.6 GB of 54.4 GB usable and takes about 31.5 h per clip.

Best precision: Q8 GGUF
Memory mode: Everything on GPU
Time per clip: 31.5 h
Output: 1280×720, 129 frames, 50 steps

Download HunyuanVideo 13B

Recommended for the AMD EPYC 7002 / 7003 series NAS (64 GB): q8_gguf. Every other precision has its own download link in the table below.

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.

Download the q8_gguf (Q8_0) file (opens in a new tab)

huggingface.co/city96/HunyuanVideo-gguf (opens in a new tab)

Original weights · Hugging Face

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

huggingface.co/tencent/HunyuanVideo (opens in a new tab)

No sign-in needed.

Official repo · GitHub

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

github.com/Tencent-Hunyuan/HunyuanVideo (opens in a new tab)

git clone https://github.com/Tencent-Hunyuan/HunyuanVideo

Links checked 3 days ago against Hugging Face, Ollama and GitHub.

How it’s rated

Quality 71Great quality (A) · 71 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking.: How capable the model itself is at Q8 GGUF, from its editorial quality tier scaled by the quantization or precision. It’s the same on any hardware that runs this variant. Scale: A+ 85+ · A 70+ · B 55+ · C 40+ · D under 40.
Runs Very slow: How well it runs on the AMD EPYC 7002 / 7003 series NAS (64 GB): speed, capped by how well it fits in memory. Runs great: 30+ tokens/s (or near the image, video or decision speed target) · Runs well: 10+ tokens/s · Slow: 3+ tokens/s · Very slow: under 3 · Won’t run: doesn’t fit even with offload. A tight fit or RAM offload caps it at Runs well; heavy offload caps it at Slow.

Match score

To order lists, each result also gets a match score out of 100 from four parts. It favors the most capable model that still runs well.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.	32.1 / 45
Memory fitFull marks when the model fits in the share of the NAS’s memory that models can use (the rest stays with the NAS system and its storage services); fewer when it goes past that limit.	25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	0.6 / 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
Match score	72.7 / 100

The match score orders results; it is not shown as a grade. Quality and Runs are the two ratings in the tables.

Every precision on the AMD EPYC 7002 / 7003 series NAS (64 GB)

Quant	Memory needed	Available	Speed	Memory mode	Runs	Quality	Download
`FP16`	48.6 GB	54.4 GB	28.8 h	Text encoder offloaded	Very slowtight fit · encoder unloaded after use	72Great quality (A) · 72 of 100: how capable the model is at FP16, whatever it runs on. Match score 66/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)
`FP8`	43.7 GB	54.4 GB	24.7 h	Everything on GPU	Very slow	70Great quality (A) · 70 of 100: how capable the model is at FP8, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking.	Original weights (opens in a new tab)
`Q8 GGUF`	44.6 GB	54.4 GB	31.5 h	Everything on GPU	Very slow	71Great quality (A) · 71 of 100: how capable the model is at Q8 GGUF, whatever it runs on. Match score 72/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)
`Q4 GGUF`	38.5 GB	54.4 GB	32.9 h	Everything on GPU	Very slow	66Good quality (B) · 66 of 100: how capable the model is at Q4 GGUF, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking.	GGUF (opens in a new tab)

Other hardware that runs it

72Great quality (A) · 72 of 100: how capable the model is at FP16, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA RTX PRO 6000 Blackwell FP16 · 29.3 min · Slow
70Great quality (A) · 70 of 100: how capable the model is at FP8, whatever it runs on. Match score 62/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GeForce RTX 5090 FP8 · 39.1 min · Slow (CPU offload)
72Great quality (A) · 72 of 100: how capable the model is at FP16, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA GH200 Grace Hopper (96 GB GPU) FP16 · 27.9 min · Slow
72Great quality (A) · 72 of 100: how capable the model is at FP16, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H100 80GB SXM FP16 · 27.9 min · Slow
72Great quality (A) · 72 of 100: how capable the model is at FP16, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H800 80GB SXM FP16 · 27.9 min · Slow
72Great quality (A) · 72 of 100: how capable the model is at FP16, whatever it runs on. Match score 77/100 (quality, fit, speed and memory use) sets the ranking. NVIDIA H100 NVL FP16 · 30.2 min · Slow

Quick answers

How much memory does HunyuanVideo 13B need on the AMD EPYC 7002 / 7003 series NAS 64GB?

At Q8 GGUF it needs about 44.6 GB. The AMD EPYC 7002 / 7003 series NAS 64GB has 54.4 GB usable.

How long does HunyuanVideo 13B take on the AMD EPYC 7002 / 7003 series NAS 64GB?

About 31.5 h per clip at Q8 GGUF and default settings, an estimate scaled from a reference timing by this hardware’s compute speed.

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.