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Can the Apple M4 Pro (48 GB) run QVQ 72B Preview?

66 ptsGood (B) · 66 of 100 points: Model quality 21.4/45, Memory fit 24.0/25, Speed 6.0/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q2_K it needs about 35.5 GB of 36.0 GB usable, with an estimated speed of 6.5 tok/s.

Best quant
Q2_K
Generation speed
6.5 tok/s
Prompt processing
77.7 tok/s
First token (1K prompt)
13.2 s
Largest safe context
9K

Download QVQ 72B Preview

Recommended for the Apple M4 Pro (48 GB): Q2_K. Every other quantization has its own download link in the table below.

Quantized files · GGUF

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

Download the Q2_K file (opens in a new tab)

huggingface.co/bartowski/QVQ-72B-Preview-GGUF (opens in a new tab)

ollama run hf.co/bartowski/QVQ-72B-Preview-GGUF:Q2_K

Original weights · Hugging Face

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

huggingface.co/Qwen/QVQ-72B-Preview (opens in a new tab)

No sign-in needed.

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.21.4 / 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.6.0 / 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
Total66.4 / 10066 ptsGood (B) · 66 of 100 points: Model quality 21.4/45, Memory fit 24.0/25, Speed 6.0/15, 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 M4 Pro (48 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 35.5 GB 36.0 GB 6.5 tok/s Tight fit 66 ptsGood (B) · 66 of 100 points: Model quality 21.4/45, Memory fit 24.0/25, Speed 6.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q3_K_M 42.1 GB 36.0 GB 4.3 tok/s Heavy offload 49 ptsUsable (C) · 49 of 100 points: Model quality 25.7/45, Memory fit 4.0/25, Speed 4.9/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q4_K_M 50.9 GB 36.0 GB — Won't run 8 ptsWon't run (F) · 8 of 100 points: Model quality 8.7/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF (opens in a new tab)
Q5_K_M 58.3 GB 36.0 GB — Won't run 8 ptsWon't run (F) · 8 of 100 points: Model quality 8.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q6_K 66.4 GB 36.0 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 9.1/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q8_0 84.0 GB 36.0 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 9.2/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
F16 153 GB 36.0 GB — Won't run 9 ptsWon't run (F) · 9 of 100 points: Model quality 9.2/45, 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.