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Can the NVIDIA RTX PRO 6000 Blackwell run Hunyuan A13B (80B-A13B)?

87 ptsExcellent (S) · 87 of 100 points: Model quality 33.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q6_K it needs about 72.4 GB of 96.0 GB usable, with an estimated speed of 58.7 tok/s.

Best quant
Q6_K
Generation speed
58.7 tok/s
Prompt processing
6,923 tok/s
First token (1K prompt)
0.3 s
Largest safe context
32K

Download Hunyuan A13B (80B-A13B)

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

huggingface.co/tencent/Hunyuan-A13B-Instruct-GGUF (opens in a new tab)

ollama run hf.co/tencent/Hunyuan-A13B-Instruct-GGUF

Original weights · Hugging Face

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

huggingface.co/tencent/Hunyuan-A13B-Instruct (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/Hunyuan-A13B (opens in a new tab)

git clone https://github.com/Tencent-Hunyuan/Hunyuan-A13B

Links checked 6 days ago against Hugging Face, Ollama and GitHub.

How the S 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.33.0 / 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.15.0 / 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
Total88.0 / 10087 ptsExcellent (S) · 87 of 100 points: Model quality 33.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

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

Every quantization on the NVIDIA RTX PRO 6000 Blackwell

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 38.6 GB 96.0 GB 139 tok/s Runs well 72 ptsGreat (A) · 72 of 100 points: Model quality 23.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.3/15 GGUF files (opens in a new tab)
Q3_K_M 45.9 GB 96.0 GB 109 tok/s Runs well 78 ptsGreat (A) · 78 of 100 points: Model quality 28.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.0/15 GGUF files (opens in a new tab)
Q4_K_M 55.5 GB 96.0 GB 84.6 tok/s Runs well 84 ptsGreat (A) · 84 of 100 points: Model quality 31.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.3/15 GGUF (opens in a new tab)
Q5_K_M 63.6 GB 96.0 GB 69.9 tok/s Runs well 87 ptsExcellent (S) · 87 of 100 points: Model quality 32.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q6_K 72.4 GB 96.0 GB 58.7 tok/s Runs well 87 ptsExcellent (S) · 87 of 100 points: Model quality 33.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q8_0 91.7 GB 96.0 GB 43.1 tok/s Tight fit 87 ptsExcellent (S) · 87 of 100 points: Model quality 33.3/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF · part 1 of 2 (opens in a new tab)
F16 167 GB 96.0 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)

Memory figures assume 8K of context. Longer conversations or documents grow the KV cache.

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.