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Can the NVIDIA RTX Spark N1X (6144-core GPU) (64 GB) 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 70/100 (quality, fit, speed and memory use) sets the ranking.

Barely: it runs very slowly (CPU offload)

Very slow (CPU offload). At FP8 it needs about 32.8 GB of 48.0 GB usable, with an estimated speed of 2.6 min.

Best precision
FP8
Memory mode
Sequential CPU offload
Time per image
2.6 min
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 70/100 (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 Very slowCPU offload
How well it runs on the NVIDIA RTX Spark N1X (6144-core GPU) (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.39.7 / 45
Memory fitFull marks when the model fits in the share of unified memory the GPU can use; fewer when it goes past that limit.12.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.3.8 / 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
Match score70.5 / 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 Spark N1X (6144-core GPU) (64 GB)

Quant Memory needed Available Speed Memory mode Runs Quality Download
FP16 61.8 GB 48.0 GB — — Won't run 90Excellent quality (A+) · 90 of 100: how capable the model is at FP16, whatever it runs on. Match score 12/100 (quality, fit, speed and memory use) sets the ranking. Original weights (opens in a new tab)
FP8 32.8 GB 48.0 GB 2.6 min Sequential CPU offload Very slowCPU offload 88Excellent quality (A+) · 88 of 100: how capable the model is at FP8, whatever it runs on. Match score 70/100 (quality, fit, speed and memory use) sets the ranking. Original weights (opens in a new tab)

Other hardware that runs it

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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