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Can the Apple M4 Max (128 GB) run Qwen3-VL 30B-A3B Thinking?

84 ptsGreat (A) · 84 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.1/15

Yes, it runs well

Runs well. At Q8_0 it needs about 42.0 GB of 96.0 GB usable, with an estimated speed of 44.5 tok/s.

Best quant
Q8_0
Generation speed
44.5 tok/s
Prompt processing
3,457 tok/s
First token (1K prompt)
0.3 s
Largest safe context
256K

Download Qwen3-VL 30B-A3B Thinking

Recommended for the Apple M4 Max (128 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.

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.10.1 / 15
Total84.3 / 10084 ptsGreat (A) · 84 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.1/15

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

Every quantization on the Apple M4 Max (128 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 21.5 GB 96.0 GB 144 tok/s Runs well 69 ptsGood (B) · 69 of 100 points: Model quality 23.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.2/15 GGUF files (opens in a new tab)
Q3_K_M 24.3 GB 96.0 GB 113 tok/s Runs well 74 ptsGreat (A) · 74 of 100 points: Model quality 28.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 5.8/15 GGUF files (opens in a new tab)
Q4_K_M 28.0 GB 96.0 GB 87.4 tok/s Runs well 79 ptsGreat (A) · 79 of 100 points: Model quality 32.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 6.7/15 GGUF (opens in a new tab)
Q5_K_M 31.1 GB 96.0 GB 72.2 tok/s Runs well 80 ptsGreat (A) · 80 of 100 points: Model quality 33.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.5/15 GGUF files (opens in a new tab)
Q6_K 34.6 GB 96.0 GB 60.7 tok/s Runs well 82 ptsGreat (A) · 82 of 100 points: Model quality 33.9/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.3/15 GGUF files (opens in a new tab)
Q8_0 42.0 GB 96.0 GB 44.5 tok/s Runs well 84 ptsGreat (A) · 84 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.1/15 GGUF (opens in a new tab)
F16 71.2 GB 96.0 GB 20.5 tok/s Runs well 84 ptsGreat (A) · 84 of 100 points: Model quality 34.2/45, Memory fit 25.0/25, Speed 10.7/15, Memory use 15.0/15 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

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.