Can the Apple M2 Pro (32 GB) run Aya Expanse 32B?

68 pts

Yes, with little memory to spare

Tight fit. At Q3_K_M it needs about 19.5 GB of 21.4 GB usable, with an estimated speed of 8.5 tok/s.

Best quant: Q3_K_M
Generation speed: 8.5 tok/s
Prompt processing: 131 tok/s
First token (1K prompt): 7.8 s
Largest safe context: 19K

Download Aya Expanse 32B

Recommended for the Apple M2 Pro (32 GB): Q3_K_M. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run aya-expanse:32b-q3_K_M

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

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

Download the Q3_K_M (Q3_K_L) file (opens in a new tab)

huggingface.co/lmstudio-community/aya-expanse-32b-GGUF (opens in a new tab)

ollama run hf.co/lmstudio-community/aya-expanse-32b-GGUF:Q3_K_L

Original weights · Hugging Face

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

huggingface.co/CohereLabs/aya-expanse-32b (opens in a new tab)

Free Hugging Face account needed: accept the license on the model page and the download starts right away.

Links checked 6 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.	22.7 / 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.	6.9 / 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
Total	68.6 / 100	68 ptsGood (B) · 68 of 100 points: Model quality 22.7/45, Memory fit 24.0/25, Speed 6.9/15, 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 M2 Pro (32 GB)

Quant	Memory needed	Available	Speed	Fit	Grade · points	Download
`Q2_K`	16.6 GB	21.4 GB	10.7 tok/s	Runs well	66 ptsGood (B) · 66 of 100 points: Model quality 18.9/45, Memory fit 25.0/25, Speed 7.8/15, Memory use 15.0/15
`Q3_K_M`	19.5 GB	21.4 GB	8.5 tok/s	Tight fit	68 ptsGood (B) · 68 of 100 points: Model quality 22.7/45, Memory fit 24.0/25, Speed 6.9/15, Memory use 15.0/15	GGUF (Q3_K_L) (opens in a new tab)
`Q4_K_M`	23.4 GB	21.4 GB	5.6 tok/s	Runs with offload	56 ptsUsable (C) · 56 of 100 points: Model quality 25.7/45, Memory fit 10.0/25, Speed 5.6/15, Memory use 15.0/15	GGUF (opens in a new tab)
`Q5_K_M`	26.6 GB	21.4 GB	4.6 tok/s	Heavy offload	50 ptsUsable (C) · 50 of 100 points: Model quality 26.2/45, Memory fit 4.0/25, Speed 5.1/15, Memory use 15.0/15
`Q6_K`	30.1 GB	21.4 GB	—	Won't run	8 ptsWon't run (F) · 8 of 100 points: Model quality 8.0/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`Q8_0`	37.9 GB	21.4 GB	—	Won't run	8 ptsWon't run (F) · 8 of 100 points: Model quality 8.1/45, Memory fit 0.0/25, Speed 0.0/15, Memory use 0.0/15	GGUF (opens in a new tab)
`F16`	68.3 GB	21.4 GB	—	Won't run	8 ptsWon't run (F) · 8 of 100 points: Model quality 8.1/45, 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

81 ptsGreat (A) · 81 of 100 points: Model quality 26.2/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 NVIDIA GeForce RTX 5090 Q5_K_M · 56.3 tok/s
79 ptsGreat (A) · 79 of 100 points: Model quality 25.7/45, Memory fit 24.0/25, Speed 14.7/15, Memory use 15.0/15 NVIDIA GeForce RTX 4090 Q4_K_M · 38.3 tok/s
78 ptsGreat (A) · 78 of 100 points: Model quality 25.7/45, Memory fit 24.0/25, Speed 14.1/15, Memory use 15.0/15 NVIDIA GeForce RTX 3090 Q4_K_M · 35.6 tok/s
77 ptsGreat (A) · 77 of 100 points: Model quality 25.7/45, Memory fit 24.0/25, Speed 13.3/15, Memory use 15.0/15 AMD Radeon RX 7900 XTX Q4_K_M · 31.4 tok/s
74 ptsGreat (A) · 74 of 100 points: Model quality 26.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 8.0/15 NVIDIA RTX PRO 6000 Blackwell Q6_K · 47.3 tok/s
72 ptsGreat (A) · 72 of 100 points: Model quality 25.7/45, Memory fit 25.0/25, Speed 10.0/15, Memory use 12.3/15 Apple M4 Max (64 GB) Q4_K_M · 17.9 tok/s

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.