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Can the NVIDIA RTX PRO 6000 Blackwell run Hermes 4.3 36B?

84 ptsGreat (A) · 84 of 100 points: Model quality 35.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.9/15

Yes, it runs well

Runs well. At Q6_K it needs about 37.2 GB of 96.0 GB usable, with an estimated speed of 42.2 tok/s.

Best quant
Q6_K
Generation speed
42.2 tok/s
Prompt processing
2,490 tok/s
First token (1K prompt)
0.4 s
Largest safe context
227K

Download Hermes 4.3 36B

Recommended for the NVIDIA RTX PRO 6000 Blackwell: Q6_K. Every other quantization has its own download link in the table below.

Quantized files · GGUF

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

Download the Q6_K file (opens in a new tab)

huggingface.co/NousResearch/Hermes-4.3-36B-GGUF (opens in a new tab)

ollama run hf.co/NousResearch/Hermes-4.3-36B-GGUF:Q6_K

Original weights · Hugging Face

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

huggingface.co/NousResearch/Hermes-4.3-36B (opens in a new tab)

No sign-in needed.

How the A 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.35.2 / 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.8.9 / 15
Total84.1 / 10084 ptsGreat (A) · 84 of 100 points: Model quality 35.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.9/15

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 22.0 GB 96.0 GB 99.9 tok/s Runs well 70 ptsGood (B) · 70 of 100 points: Model quality 24.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.3/15 GGUF files (opens in a new tab)
Q3_K_M 25.3 GB 96.0 GB 78.7 tok/s Runs well 75 ptsGreat (A) · 75 of 100 points: Model quality 29.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.1/15 GGUF (opens in a new tab)
Q4_K_M 29.6 GB 96.0 GB 60.9 tok/s Runs well 80 ptsGreat (A) · 80 of 100 points: Model quality 33.8/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.1/15 GGUF (opens in a new tab)
Q5_K_M 33.2 GB 96.0 GB 50.3 tok/s Runs well 82 ptsGreat (A) · 82 of 100 points: Model quality 34.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.0/15 GGUF (opens in a new tab)
Q6_K 37.2 GB 96.0 GB 42.2 tok/s Runs well 84 ptsGreat (A) · 84 of 100 points: Model quality 35.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.9/15 GGUF (opens in a new tab)
Q8_0 45.9 GB 96.0 GB 31.0 tok/s Runs well 84 ptsGreat (A) · 84 of 100 points: Model quality 35.6/45, Memory fit 25.0/25, Speed 13.2/15, Memory use 11.0/15 GGUF (opens in a new tab)
F16 79.8 GB 96.0 GB 14.3 tok/s Runs well 84 ptsGreat (A) · 84 of 100 points: Model quality 35.6/45, Memory fit 25.0/25, Speed 9.0/15, Memory use 15.0/15 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.