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Can the Apple M5 Max (64 GB) run GLM-4.6V?

65 ptsGood (B) · 65 of 100 points: Model quality 26.1/45, Memory fit 10.0/25, Speed 14.6/15, Memory use 15.0/15

Yes, with part of the model in system RAM

Runs with offload. At Q2_K it needs about 49.1 GB of 48.0 GB usable, with an estimated speed of 37.8 tok/s.

Best quant
Q2_K
Generation speed
37.8 tok/s
Prompt processing
977 tok/s
First token (1K prompt)
1.0 s
Largest safe context
2K

Download GLM-4.6V

Recommended for the Apple M5 Max (64 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/unsloth/GLM-4.6V-GGUF (opens in a new tab)

ollama run hf.co/unsloth/GLM-4.6V-GGUF:Q2_K

Original weights · Hugging Face

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

huggingface.co/zai-org/GLM-4.6V (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.26.1 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.10.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.14.6 / 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
Total65.7 / 10065 ptsGood (B) · 65 of 100 points: Model quality 26.1/45, Memory fit 10.0/25, Speed 14.6/15, 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 49.1 GB 48.0 GB 37.8 tok/s Runs with offload 65 ptsGood (B) · 65 of 100 points: Model quality 26.1/45, Memory fit 10.0/25, Speed 14.6/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q3_K_M 58.8 GB 48.0 GB 29.7 tok/s Heavy offload 63 ptsGood (B) · 63 of 100 points: Model quality 31.4/45, Memory fit 4.0/25, Speed 12.9/15, Memory use 15.0/15 GGUF · folder (opens in a new tab)
Q4_K_M 71.7 GB 48.0 GB — Won't run 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q5_K_M 82.5 GB 48.0 GB — Won't run 10 ptsWon't run (F) · 10 of 100 points: Model quality 10.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q6_K 94.3 GB 48.0 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.1/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
Q8_0 120 GB 48.0 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.2/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (opens in a new tab)
F16 221 GB 48.0 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.2/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF · folder (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.