Qwen3 235B-A22B Instruct 2507 on Apple M2 Ultra (192 GB)

Can the Apple M2 Ultra (192 GB) run Qwen3 235B-A22B Instruct 2507?

84 pts

Yes, with little memory to spare

Tight fit. At Q3_K_M it needs about 129 GB of 144 GB usable, with an estimated speed of 24.8 tok/s.

Best quant: Q3_K_M
Generation speed: 24.8 tok/s
Prompt processing: 767 tok/s
First token (1K prompt): 1.3 s
Largest safe context: 84K

Download Qwen3 235B-A22B Instruct 2507

Recommended for the Apple M2 Ultra (192 GB): Q3_K_M. 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 Q3_K_M 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 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.	34.0 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.	24.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.	11.8 / 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
Total	84.8 / 100	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

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

Every quantization on the Apple M2 Ultra (192 GB)

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	108 GB	144 GB	31.6 tok/s	Runs well	81 ptsGreat (A) · 81 of 100 points: Model quality 28.4/45, Memory fit 25.0/25, Speed 13.3/15, Memory use 15.0/15	GGUF · folder (opens in a new tab)
`Q3_K_M`	129 GB	144 GB	24.8 tok/s	Tight fit	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	GGUF · folder (opens in a new tab)
`Q4_K_M`	157 GB	144 GB	16.3 tok/s	Runs with offload	73 ptsGreat (A) · 73 of 100 points: Model quality 38.5/45, Memory fit 10.0/25, Speed 9.6/15, Memory use 15.0/15	GGUF · folder (opens in a new tab)
`Q5_K_M`	181 GB	144 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`	206 GB	144 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`	263 GB	144 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`	484 GB	144 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 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
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 NVIDIA RTX PRO 6000 Blackwell Q2_K · 34.5 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.