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Can the Apple M2 Pro (32 GB) run Qwen3 30B-A3B?

82 ptsGreat (A) · 82 of 100 points: Model quality 28.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q3_K_M it needs about 18.1 GB of 21.4 GB usable, with an estimated speed of 41.4 tok/s.

Best quant
Q3_K_M
Generation speed
41.4 tok/s
Prompt processing
1,278 tok/s
First token (1K prompt)
0.8 s
Largest safe context
32K

Download Qwen3 30B-A3B

Quickest · Ollama

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

ollama run qwen3:30b

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.

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

ollama run hf.co/Qwen/Qwen3-30B-A3B-GGUF

Original weights · Hugging Face

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

huggingface.co/Qwen/Qwen3-30B-A3B (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

Links checked 7 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.28.0 / 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.15.0 / 15
Total83.0 / 10082 ptsGreat (A) · 82 of 100 points: Model quality 28.0/45, Memory fit 25.0/25, Speed 15.0/15, 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 Pro (32 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 15.3 GB 21.4 GB 52.6 tok/s Runs well 78 ptsGreat (A) · 78 of 100 points: Model quality 23.3/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q3_K_M 18.1 GB 21.4 GB 41.4 tok/s Runs well 82 ptsGreat (A) · 82 of 100 points: Model quality 28.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q4_K_M 21.7 GB 21.4 GB 27.2 tok/s Runs with offload 69 ptsGood (B) · 69 of 100 points: Model quality 31.6/45, Memory fit 10.0/25, Speed 12.4/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 24.8 GB 21.4 GB 22.5 tok/s Heavy offload 62 ptsGood (B) · 62 of 100 points: Model quality 32.3/45, Memory fit 4.0/25, Speed 11.2/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q6_K 28.1 GB 21.4 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 9.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (opens in a new tab)
Q8_0 35.5 GB 21.4 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 10.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (opens in a new tab)
F16 64.1 GB 21.4 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 10.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 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.