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Can the Apple M2 Ultra (192 GB) run InternVL3.5 241B-A28B?

81 ptsGreat (A) · 81 of 100 points: Model quality 32.5/45, Memory fit 24.0/25, Speed 10.5/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q3_K_M it needs about 132 GB of 144 GB usable, with an estimated speed of 19.5 tok/s.

Best quant
Q3_K_M
Generation speed
19.5 tok/s
Prompt processing
602 tok/s
First token (1K prompt)
1.7 s
Largest safe context
40K

Download InternVL3.5 241B-A28B

Quantized files · GGUF

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

huggingface.co/mradermacher/InternVL3_5-241B-A28B-GGUF (opens in a new tab)

ollama run hf.co/mradermacher/InternVL3_5-241B-A28B-GGUF

Original weights · Hugging Face

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

huggingface.co/OpenGVLab/InternVL3_5-241B-A28B (opens in a new tab)

No sign-in needed.

Links checked 6 hours 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.32.5 / 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.10.5 / 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
Total82.0 / 10081 ptsGreat (A) · 81 of 100 points: Model quality 32.5/45, Memory fit 24.0/25, Speed 10.5/15, 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 Ultra (192 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 110 GB 144 GB 24.8 tok/s Runs well 78 ptsGreat (A) · 78 of 100 points: Model quality 27.1/45, Memory fit 25.0/25, Speed 11.8/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q3_K_M 132 GB 144 GB 19.5 tok/s Tight fit 81 ptsGreat (A) · 81 of 100 points: Model quality 32.5/45, Memory fit 24.0/25, Speed 10.5/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q4_K_M 161 GB 144 GB 12.8 tok/s Heavy offload 64 ptsGood (B) · 64 of 100 points: Model quality 36.8/45, Memory fit 4.0/25, Speed 8.5/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q5_K_M 185 GB 144 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.3/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF files (opens in a new tab)
Q6_K 211 GB 144 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.5/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF files (opens in a new tab)
Q8_0 269 GB 144 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.6/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF files (opens in a new tab)
F16 495 GB 144 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.6/45, 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.