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Can the Apple M4 Pro (48 GB) run Apodex 1.1 Mini (35B-A3B)?

93 ptsExcellent (S) · 93 of 100 points: Model quality 38.8/45, Memory fit 25.0/25, Speed 14.9/15, Memory use 15.0/15

Yes, it runs well

Runs well. At Q5_K_M it needs about 29.2 GB of 36.0 GB usable, with an estimated speed of 39.7 tok/s.

Best quant
Q5_K_M
Generation speed
39.7 tok/s
Prompt processing
1,901 tok/s
First token (1K prompt)
0.5 s
Largest safe context
256K

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 42 minutes 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.38.8 / 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.14.9 / 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
Total93.8 / 10093 ptsExcellent (S) · 93 of 100 points: Model quality 38.8/45, Memory fit 25.0/25, Speed 14.9/15, 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 M4 Pro (48 GB)

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 18.0 GB 36.0 GB 79.0 tok/s Runs well 79 ptsGreat (A) · 79 of 100 points: Model quality 28.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 11.6/15 GGUF files (opens in a new tab)
Q3_K_M 21.3 GB 36.0 GB 62.2 tok/s Runs well 87 ptsExcellent (S) · 87 of 100 points: Model quality 33.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.6/15 GGUF files (opens in a new tab)
Q4_K_M 25.6 GB 36.0 GB 48.1 tok/s Runs well 93 ptsExcellent (S) · 93 of 100 points: Model quality 38.0/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 GGUF (opens in a new tab)
Q5_K_M 29.2 GB 36.0 GB 39.7 tok/s Runs well 93 ptsExcellent (S) · 93 of 100 points: Model quality 38.8/45, Memory fit 25.0/25, Speed 14.9/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q6_K 33.1 GB 36.0 GB 33.4 tok/s Tight fit 92 ptsExcellent (S) · 92 of 100 points: Model quality 39.6/45, Memory fit 24.0/25, Speed 13.7/15, Memory use 15.0/15 GGUF files (opens in a new tab)
Q8_0 41.8 GB 36.0 GB 20.8 tok/s Heavy offload 69 ptsGood (B) · 69 of 100 points: Model quality 40.1/45, Memory fit 4.0/25, Speed 10.8/15, Memory use 15.0/15 GGUF files (opens in a new tab)
F16 75.5 GB 36.0 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.