Qwen3 235B-A22B Instruct 2507 on NVIDIA RTX PRO 6000 Blackwell

Can the NVIDIA RTX PRO 6000 Blackwell run Qwen3 235B-A22B Instruct 2507?

67 pts

Yes, with part of the model in system RAM

Runs with offload. At Q2_K it needs about 101 GB of 96.0 GB usable, with an estimated speed of 34.5 tok/s.

Best quant: Q2_K
Generation speed: 34.5 tok/s
Prompt processing: 3,938 tok/s
First token (1K prompt): 0.3 s
Largest safe context: —

Download Qwen3 235B-A22B Instruct 2507

Recommended for the NVIDIA RTX PRO 6000 Blackwell: Q2_K. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run qwen3:235b-instruct

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

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

Download the Q2_K files (opens in a new tab)

huggingface.co/unsloth/Qwen3-235B-A22B-Instruct-2507-GGUF (opens in a new tab)

ollama run hf.co/unsloth/Qwen3-235B-A22B-Instruct-2507-GGUF

Original weights · Hugging Face

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

huggingface.co/Qwen/Qwen3-235B-A22B-Instruct-2507 (opens in a new tab)

No sign-in needed.

Official repo · GitHub

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

github.com/QwenLM/Qwen3 (opens in a new tab)

git clone https://github.com/QwenLM/Qwen3

Qwen’s main repo, renamed from Qwen2.5 to Qwen3; it still documents Qwen2.5.

Links checked 5 days ago against Hugging Face, Ollama and GitHub.

How the B 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.	28.4 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	10.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	13.9 / 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
Total	67.3 / 100	67 ptsGood (B) · 67 of 100 points: Model quality 28.4/45, Memory fit 10.0/25, Speed 13.9/15, 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`	101 GB	96.0 GB	34.5 tok/s	Runs with offload	67 ptsGood (B) · 67 of 100 points: Model quality 28.4/45, Memory fit 10.0/25, Speed 13.9/15, Memory use 15.0/15	GGUF · folder (opens in a new tab)
`Q3_K_M`	122 GB	96.0 GB	—	Won't run	10 ptsWon't run (F) · 10 of 100 points: Model quality 10.2/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · folder (opens in a new tab)
`Q4_K_M`	150 GB	96.0 GB	—	Won't run	11 ptsWon't run (F) · 11 of 100 points: Model quality 11.5/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · folder (opens in a new tab)
`Q5_K_M`	174 GB	96.0 GB	—	Won't run	11 ptsWon't run (F) · 11 of 100 points: Model quality 11.8/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · folder (opens in a new tab)
`Q6_K`	200 GB	96.0 GB	—	Won't run	12 ptsWon't run (F) · 12 of 100 points: Model quality 12.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · folder (opens in a new tab)
`Q8_0`	256 GB	96.0 GB	—	Won't run	12 ptsWon't run (F) · 12 of 100 points: Model quality 12.2/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · folder (opens in a new tab)
`F16`	477 GB	96.0 GB	—	Won't run	12 ptsWon't run (F) · 12 of 100 points: Model quality 12.2/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF · folder (opens in a new tab) 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

88 ptsExcellent (S) · 88 of 100 points: Model quality 38.5/45, Memory fit 25.0/25, Speed 10.5/15, Memory use 15.0/15 Apple M3 Ultra (256 GB) Q4_K_M · 19.7 tok/s
84 ptsGreat (A) · 84 of 100 points: Model quality 34.0/45, Memory fit 24.0/25, Speed 11.8/15, Memory use 15.0/15 Apple M2 Ultra (192 GB) Q3_K_M · 24.8 tok/s
84 ptsGreat (A) · 84 of 100 points: Model quality 38.5/45, Memory fit 25.0/25, Speed 10.5/15, Memory use 10.6/15 Apple M3 Ultra (512 GB) Q4_K_M · 19.7 tok/s
75 ptsGreat (A) · 75 of 100 points: Model quality 28.4/45, Memory fit 24.0/25, Speed 8.4/15, Memory use 15.0/15 NVIDIA GB10 (128 GB) Q2_K · 12.5 tok/s
63 ptsGood (B) · 63 of 100 points: Model quality 28.4/45, Memory fit 10.0/25, Speed 10.1/15, Memory use 15.0/15 Apple M4 Max (128 GB) Q2_K · 18.3 tok/s

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.