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Can the Apple M5 Max (64 GB) run CogVLM2 Llama 3 Chat 19B?

64 ptsGood (B) · 64 of 100 points: Model quality 16.2/45, Memory fit 25.0/25, Speed 13.7/15, Memory use 9.9/15

Yes, it runs well

Runs well. At Q4_K_M it needs about 20.6 GB of 48.0 GB usable, with an estimated speed of 33.3 tok/s.

Best quant
Q4_K_M
Generation speed
33.3 tok/s
Prompt processing
601 tok/s
First token (1K prompt)
1.7 s
Largest safe context
8K

Download CogVLM2 Llama 3 Chat 19B

Original weights · Hugging Face

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

huggingface.co/zai-org/cogvlm2-llama3-chat-19B (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.16.2 / 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.13.7 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.9.9 / 15
Total64.8 / 10064 ptsGood (B) · 64 of 100 points: Model quality 16.2/45, Memory fit 25.0/25, Speed 13.7/15, Memory use 9.9/15

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 16.5 GB 48.0 GB 54.7 tok/s Runs well 59 ptsGood (B) · 59 of 100 points: Model quality 12.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.9/15 All files (opens in a new tab)
Q3_K_M 18.3 GB 48.0 GB 43.0 tok/s Runs well 63 ptsGood (B) · 63 of 100 points: Model quality 14.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.8/15 All files (opens in a new tab)
Q4_K_M 20.6 GB 48.0 GB 33.3 tok/s Runs well 64 ptsGood (B) · 64 of 100 points: Model quality 16.2/45, Memory fit 25.0/25, Speed 13.7/15, Memory use 9.9/15 All files (opens in a new tab)
Q5_K_M 22.6 GB 48.0 GB 27.5 tok/s Runs well 64 ptsGood (B) · 64 of 100 points: Model quality 16.6/45, Memory fit 25.0/25, Speed 12.4/15, Memory use 10.9/15 All files (opens in a new tab)
Q6_K 24.7 GB 48.0 GB 23.1 tok/s Runs well 65 ptsGood (B) · 65 of 100 points: Model quality 16.9/45, Memory fit 25.0/25, Speed 11.4/15, Memory use 11.9/15 All files (opens in a new tab)
Q8_0 29.4 GB 48.0 GB 16.9 tok/s Runs well 65 ptsGood (B) · 65 of 100 points: Model quality 17.1/45, Memory fit 25.0/25, Speed 9.8/15, Memory use 14.1/15 All files (opens in a new tab)
F16 47.7 GB 48.0 GB 7.8 tok/s Tight fit 62 ptsGood (B) · 62 of 100 points: Model quality 17.1/45, Memory fit 24.0/25, Speed 6.6/15, Memory use 15.0/15 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.