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Can the NVIDIA RTX PRO 5000 Blackwell 72GB run HunyuanImage 3.0 (80B-A13B)?

88Excellent quality (A+) · 88 of 100: how capable the model is at FP8, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking.

Yes, but slowly (CPU offload)

Slow (CPU offload). At FP8 it needs about 32.8 GB of 72.0 GB usable and takes about 84 s per image.

Best precision
FP8
Memory mode
Sequential CPU offload
Time per image
84 s
Output
1024×1024, 50 steps

Download HunyuanImage 3.0 (80B-A13B)

Original weights · Hugging Face

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

huggingface.co/tencent/HunyuanImage-3.0 (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/HunyuanImage-3.0 (opens in a new tab)

git clone https://github.com/Tencent-Hunyuan/HunyuanImage-3.0

How it’s rated

Quality 88Excellent quality (A+) · 88 of 100: how capable the model is at FP8, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking.
How capable the model itself is at FP8, 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 SlowCPU offload
How well it runs on the NVIDIA RTX PRO 5000 Blackwell 72GB: 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.39.7 / 45
Memory fitFull marks when everything sits in GPU memory; fewer when part spills to system RAM.12.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.5.2 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.10.5 / 15
Match score67.4 / 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 NVIDIA RTX PRO 5000 Blackwell 72GB

Quant Memory needed Available Speed Memory mode Runs Quality Download
FP16 61.8 GB 72.0 GB 1.6 min Sequential CPU offload Slowtight fit · CPU offload 90Excellent quality (A+) · 90 of 100: how capable the model is at FP16, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. Original weights (opens in a new tab)
FP8 32.8 GB 72.0 GB 84 s Sequential CPU offload SlowCPU offload 88Excellent quality (A+) · 88 of 100: how capable the model is at FP8, whatever it runs on. Match score 67/100 (quality, fit, speed and memory use) sets the ranking. Original weights (opens in a new tab)

Other hardware that runs it

Quick answers

How much memory does HunyuanImage 3.0 (80B-A13B) need on the NVIDIA RTX PRO 5000 Blackwell 72GB?

At FP8 it needs about 32.8 GB. The NVIDIA RTX PRO 5000 Blackwell 72GB has 72.0 GB usable.

How long does HunyuanImage 3.0 (80B-A13B) take on the NVIDIA RTX PRO 5000 Blackwell 72GB?

About 84 s per image at FP8 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.

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