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Can the Apple M2 Pro (32 GB) run Apodex 1.1 Mini (35B-A3B)?

87 ptsExcellent (S) · 87 of 100 points: Model quality 33.6/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15

Yes, with little memory to spare

Tight fit. At Q3_K_M it needs about 20.1 GB of 21.4 GB usable, with an estimated speed of 45.6 tok/s.

Best quant
Q3_K_M
Generation speed
45.6 tok/s
Prompt processing
1,405 tok/s
First token (1K prompt)
0.7 s
Largest safe context
71K

Download Apodex 1.1 Mini (35B-A3B)

Quantized files · GGUF

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

huggingface.co/apodex/Apodex-1.1-mini-GGUF (opens in a new tab)

ollama run hf.co/apodex/Apodex-1.1-mini-GGUF

Original weights · Hugging Face

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

huggingface.co/apodex/Apodex-1.1-mini (opens in a new tab)

No sign-in needed.

Links checked 6 days ago against Hugging Face, Ollama and GitHub.

How the S 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.33.6 / 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.15.0 / 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
Total87.6 / 10087 ptsExcellent (S) · 87 of 100 points: Model quality 33.6/45, Memory fit 24.0/25, Speed 15.0/15, 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 M2 Pro (32 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 16.9 GB 21.4 GB 57.9 tok/s Runs well 83 ptsGreat (A) · 83 of 100 points: Model quality 28.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q3_K_M 20.1 GB 21.4 GB 45.6 tok/s Tight fit 87 ptsExcellent (S) · 87 of 100 points: Model quality 33.6/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q4_K_M 24.4 GB 21.4 GB 29.9 tok/s Heavy offload 70 ptsGood (B) · 70 of 100 points: Model quality 38.0/45, Memory fit 4.0/25, Speed 13.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 28.0 GB 21.4 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.7/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF files (opens in a new tab)
Q6_K 32.0 GB 21.4 GB — Won't run 11 ptsWon't run (F) · 11 of 100 points: Model quality 11.9/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF files (opens in a new tab)
Q8_0 40.6 GB 21.4 GB — Won't run 12 ptsWon't run (F) · 12 of 100 points: Model quality 12.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15 GGUF files (opens in a new tab)
F16 74.4 GB 21.4 GB — Won't run 12 ptsWon't run (F) · 12 of 100 points: Model quality 12.0/45, 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.