Qwen3-VL 30B-A3B Thinking on Apple M2 Ultra (192 GB)

Can the Apple M2 Ultra (192 GB) run Qwen3-VL 30B-A3B Thinking?

81 pts

Yes, it runs well

Runs well. At Q8_0 it needs about 45.9 GB of 144 GB usable, with an estimated speed of 65.2 tok/s.

Best quant: Q8_0
Generation speed: 65.2 tok/s
Prompt processing: 5,110 tok/s
First token (1K prompt): 0.3 s
Largest safe context: 256K

Download Qwen3-VL 30B-A3B Thinking

Recommended for the Apple M2 Ultra (192 GB): Q8_0. 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-vl:30b-a3b-thinking-q8_0

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 Q8_0 file (opens in a new tab)

huggingface.co/Qwen/Qwen3-VL-30B-A3B-Thinking-GGUF (opens in a new tab)

ollama run hf.co/Qwen/Qwen3-VL-30B-A3B-Thinking-GGUF:Q8_0

Original weights · Hugging Face

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

huggingface.co/Qwen/Qwen3-VL-30B-A3B-Thinking (opens in a new tab)

No sign-in needed.

Links checked 6 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.	34.2 / 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.	7.3 / 15
Total	81.5 / 100	81 ptsGreat (A) · 81 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.3/15

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`	25.4 GB	144 GB	210 tok/s	Runs well	68 ptsGood (B) · 68 of 100 points: Model quality 23.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.1/15	GGUF files (opens in a new tab)
`Q3_K_M`	28.1 GB	144 GB	166 tok/s	Runs well	73 ptsGreat (A) · 73 of 100 points: Model quality 28.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 4.5/15	GGUF files (opens in a new tab)
`Q4_K_M`	31.9 GB	144 GB	128 tok/s	Runs well	77 ptsGreat (A) · 77 of 100 points: Model quality 32.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.1/15	GGUF (opens in a new tab)
`Q5_K_M`	35.0 GB	144 GB	106 tok/s	Runs well	78 ptsGreat (A) · 78 of 100 points: Model quality 33.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.6/15	GGUF files (opens in a new tab)
`Q6_K`	38.4 GB	144 GB	88.9 tok/s	Runs well	80 ptsGreat (A) · 80 of 100 points: Model quality 33.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.2/15	GGUF files (opens in a new tab)
`Q8_0`	45.9 GB	144 GB	65.2 tok/s	Runs well	81 ptsGreat (A) · 81 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.3/15	GGUF (opens in a new tab)
`F16`	75.1 GB	144 GB	30.1 tok/s	Runs well	84 ptsGreat (A) · 84 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 13.0/15, Memory use 12.0/15	GGUF · part 1 of 2 (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

89 ptsExcellent (S) · 89 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 Apple M4 Max (64 GB) Q8_0 · 44.5 tok/s
89 ptsExcellent (S) · 89 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA RTX PRO 6000 Blackwell F16 · 78.2 tok/s
88 ptsExcellent (S) · 88 of 100 points: Model quality 33.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.8/15 Apple M1 Max (64 GB) Q6_K · 44.4 tok/s
88 ptsExcellent (S) · 88 of 100 points: Model quality 33.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 Q5_K_M · 275 tok/s
87 ptsExcellent (S) · 87 of 100 points: Model quality 32.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 14.9/15 Apple M4 Pro (48 GB) Q4_K_M · 43.7 tok/s
86 ptsExcellent (S) · 86 of 100 points: Model quality 32.5/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX Q4_K_M · 154 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.