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Can the Apple M5 Max (64 GB) run Qwen2-VL 72B Instruct?

71 ptsGood (B) · 71 of 100 points: Model quality 24.2/45, Memory fit 24.0/25, Speed 8.0/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q3_K_M it needs about 43.1 GB of 48.0 GB usable, with an estimated speed of 11.4 tok/s.

Best quant
Q3_K_M
Generation speed
11.4 tok/s
Prompt processing
160 tok/s
First token (1K prompt)
6.4 s
Largest safe context
22K

Download Qwen2-VL 72B Instruct

Recommended for the Apple M5 Max (64 GB): Q3_K_M. 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 Q3_K_M file (opens in a new tab)

huggingface.co/bartowski/Qwen2-VL-72B-Instruct-GGUF (opens in a new tab)

ollama run hf.co/bartowski/Qwen2-VL-72B-Instruct-GGUF:Q3_K_M

Original weights · Hugging Face

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

huggingface.co/Qwen/Qwen2-VL-72B-Instruct (opens in a new tab)

No sign-in needed.

Links checked 7 days ago against Hugging Face, Ollama and GitHub.

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.24.2 / 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.8.0 / 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
Total71.2 / 10071 ptsGood (B) · 71 of 100 points: Model quality 24.2/45, Memory fit 24.0/25, Speed 8.0/15, 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 M5 Max (64 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 36.5 GB 48.0 GB 14.5 tok/s Runs well 69 ptsGood (B) · 69 of 100 points: Model quality 20.2/45, Memory fit 25.0/25, Speed 9.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q3_K_M 43.1 GB 48.0 GB 11.4 tok/s Tight fit 71 ptsGood (B) · 71 of 100 points: Model quality 24.2/45, Memory fit 24.0/25, Speed 8.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q4_K_M 51.9 GB 48.0 GB 7.5 tok/s Runs with offload 58 ptsGood (B) · 58 of 100 points: Model quality 27.4/45, Memory fit 10.0/25, Speed 6.5/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 59.2 GB 48.0 GB — Won't run 8 ptsWon't run (F) · 8 of 100 points: Model quality 8.4/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q6_K 67.3 GB 48.0 GB — Won't run 8 ptsWon't run (F) · 8 of 100 points: Model quality 8.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q8_0 84.9 GB 48.0 GB — Won't run 8 ptsWon't run (F) · 8 of 100 points: Model quality 8.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
F16 154 GB 48.0 GB — Won't run 8 ptsWon't run (F) · 8 of 100 points: Model quality 8.6/45, 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.