Macs

Which AI models run on the M5 (32 GB, 10-core GPU)?

The M5 (32 GB, 10-core GPU) has 32 GB of memory, about 21 GB of it usable for a model, and 153 GB/s of memory bandwidth. 70 of the 110 models in our catalog run on it at 4-bit or better.

Data as of 2 November 2026 · Vendor specs

Compare with other machines

32 GBmemory ~21 GB usable for a model

153 GB/sbandwidth, sets the speed

70models run at 4-bit or better

Our pick for this machine Qwen3-Coder-30B-A3B Q4_K_M · 20 of 21 GB · ~37 tok/s ModelFit est. The largest model on our shortlist of current models that runs at 4-bit or better and 10 tok/s or more.

Models that run on it

Model	Best build	Memory	Speed
Qwen3-Coder-30B-A3B30.5B MoE	Q4_K_M	20 GB	~37 tok/s ModelFit est.
Nemotron 3 Nano 30B-A3B30B MoE	Q4_K_M	19.6 GB	~46 tok/s our est.
Qwen3.8-27B27.3B	Q4_K_M	17.9 GB	~8.3 tok/s slow ModelFit est.
Gemma 4 26B-A4B25.2B MoE	Q4_K_M	17.4 GB	~32 tok/s ModelFit est.
gpt-oss-20b21B MoE	MXFP4	15.1 GB	~32 tok/s ModelFit est.
Nemotron Nano 9B v29B	Q6_K	8.6 GB	~11 tok/s our est.
Qwen3.5 9B Instruct9B	Q8_0	12.0 GB	~16 tok/s ModelFit est.
Qwen2.5 7B Instruct7B	Q4_K_M	6.6 GB	~29 tok/s ModelFit est.
Gemma 3 4B Instruct4B	Q8_0	5.0 GB	~30 tok/s ModelFit est.
Olmo 3.1 32B Instruct32B	Q4_K_M	21 GB	~6.6 tok/s slow ModelFit est.
Cohere North Mini Code30B	Q4_K_M	20 GB	no estimate
Nemotron 3.5 Lightning 30B-A3B30B MoE	IQ4_XS	20 GB	~45 tok/s our est.
GLM-4.7-Flash 30B-A3B30B MoE	Q4_K_M	20 GB	~35 tok/s ModelFit est.
Muse Glimmer 30B29.8B	Q4_K_M	18.3 GB	~8.4 tok/s slow ModelFit est.
Granite 4.2 30B29.3B	Q4_K_M	17.9 GB	~7.2 tok/s slow ModelFit est.
AREX-2 27B27.4B	Q4_K_M	18.6 GB	~8.1 tok/s slow ModelFit est.
Qwen3.5 27B Instruct27B	Q4_K_M	17.4 GB	~8.4 tok/s slow ModelFit est.
Qwen3.6 27B27B	Q4_K_M	19.4 GB	~8.3 tok/s slow ModelFit est.
Jebadiah 27B27B	Q4_K_M	18.2 GB	~8.3 tok/s slow ModelFit est.
Mistral Small 3.124B	Q4_K_M	16.4 GB	~5.6 tok/s slow our est.
LFM2 24B-A2B Instruct24B MoE	Q4_K_M	15.3 GB	~57 tok/s ModelFit est.
Devstral Small 2 24B24B	Q4_K_M	16.6 GB	~8.7 tok/s slow ModelFit est.
Mistral Small 22B22B	Q4_K_M	18.4 GB	~10 tok/s ModelFit est.
Qwen2.5 14B Instruct14B	Q4_K_M	12.3 GB	~14 tok/s ModelFit est.
Phi-3 Medium 14B14B	Q4_K_M	12.3 GB	~7.7 tok/s slow our est.
Phi-4 14B14B	Q4_K_M	12.8 GB	~14 tok/s ModelFit est.
Qwen2.5 Coder 14B14B	Q4_K_M	12.3 GB	~14 tok/s ModelFit est.
Qwen3 14B14B	Q4_K_M	12.3 GB	~14 tok/s ModelFit est.
DeepSeek-R1 Distill Qwen 14B14B	Q4_K_M	12.3 GB	~14 tok/s ModelFit est.
Ministral 3 14B13.5B	Q4_K_M	10.3 GB	~14 tok/s ModelFit est.
Mellum2.1 12B-A2.5B Thinking12.1B MoE	Q4_K_M	9.3 GB	~50 tok/s our est.
Mistral Nemo 12B12B	Q8_0	13.4 GB	~10 tok/s ModelFit est.
Gemma 3 12B Instruct12B	Q4_K_M	10.7 GB	~17 tok/s ModelFit est.
Gemma 4 12B12B	Q8_0	14.1 GB	~10 tok/s ModelFit est.
GLM-4-9B-Chat9.4B	Q8_0	11.2 GB	~14 tok/s ModelFit est.
Gemma 2 9B Instruct9B	Q4_K_M	8.2 GB	~18 tok/s ModelFit est.
Ornith 1.0 9B9B	Q4_K_M	6.7 GB	~26 tok/s ModelFit est.
MiMo-V2.6-Distill-Qwen-9B9B	Q4_K_M	6.9 GB	~25 tok/s ModelFit est.
Jebadiah 9B9B	Q8_0	11.0 GB	~15 tok/s ModelFit est.
Granite 4.2 8B8.8B	Q4_K_M	6.1 GB	~23 tok/s ModelFit est.
Granite Switch 4.1 8B8.8B	Q4_K_M	7.6 GB	~19 tok/s ModelFit est.
MiniCPM-V 4.5 8B8.7B	Q4_K_M	6.8 GB	~25 tok/s ModelFit est.
Ministral 3 8B8.4B	Q4_K_M	7.1 GB	~21 tok/s ModelFit est.
LFM2.5 8B-A1B8.3B MoE	Q4_K_M	6.6 GB	~75 tok/s ModelFit est.
Llama 3.1 8B Instruct8B	Q8_0	9.2 GB	~16 tok/s ModelFit est.
Qwen3 8B8B	Q8_0	9.3 GB	~15 tok/s ModelFit est.
Granite 4.1 8B Instruct8B	Q4_K_M	6.6 GB	~22 tok/s ModelFit est.
Mistral 7B Instruct7B	Q8_0	8.4 GB	~16 tok/s ModelFit est.
Qwen2.5 Coder 7B7B	Q4_K_M	6.6 GB	~29 tok/s ModelFit est.
DeepSeek-R1 Distill Qwen 7B7B	Q8_0	8.7 GB	~17 tok/s ModelFit est.
Gemma 4 E4B4.5B	Q8_0	8.7 GB	~26 tok/s ModelFit est.
Qwen3.5 4B Instruct4B	Q8_0	5.4 GB	~29 tok/s ModelFit est.
NVIDIA Nemotron 3.5 Bolt E4B4B	Q4_K_M	9.1 GB	~34 tok/s ModelFit est.
Phi-3 Mini 3.8B3.8B	Q4_K_M	4.3 GB	~26 tok/s our est.
Phi-4 Mini 3.8B3.8B	Q8_0	4.9 GB	~28 tok/s ModelFit est.
Granite 4.2 3B3.7B	Q4_K_M	3.2 GB	~53 tok/s ModelFit est.
Ministral 3 3B3.4B	Q4_K_M	4.1 GB	~38 tok/s ModelFit est.
Qwen2.5 3B Instruct3B	Q4_K_M	3.6 GB	~61 tok/s ModelFit est.
Llama 3.2 3B Instruct3B	Q4_K_M	3.6 GB	~51 tok/s ModelFit est.
Granite 4.1 3B Instruct3B	Q4_K_M	3.0 GB	~52 tok/s ModelFit est.
Gemma 4 E2B2.3B	Q8_0	5.7 GB	~61 tok/s ModelFit est.
Gemma 2 2B Instruct2B	Q4_K_M	2.8 GB	~59 tok/s ModelFit est.
Qwen3.5 2B Instruct2B	Q4_K_M	2.8 GB	~62 tok/s ModelFit est.
LFM3 1.7B1.73B	Q4_K_M	2.1 GB	~105 tok/s ModelFit est.
Qwen2.5 1.5B Instruct1.5B	Q4_K_M	2.5 GB	~109 tok/s ModelFit est.
Llama 3.2 1B Instruct1B	Q4_K_M	2.0 GB	~125 tok/s ModelFit est.
Gemma 3 1B Instruct1B	Q8_0	2.0 GB	~110 tok/s ModelFit est.
Qwen3.5 0.8B Instruct0.8B	Q4_K_M	1.8 GB	~135 tok/s ModelFit est.
Qwen2.5 0.5B Instruct0.5B	Q4_K_M	1.8 GB	~231 tok/s ModelFit est.
SmolLM2 360M0.36B	Q4_K_M	1.5 GB	~131 tok/s ModelFit est.

Speeds come from ModelFit's estimates (CC BY 4.0) where it covers the model, otherwise from our bandwidth formula. Method

Fits only at 3-bit or lower

Llama 3.3 Nemotron Super 49B.

Too big for this machine

DeepSeek-R1 Distill Qwen 32B (21 GB), Gemma 4 31B (21 GB), Qwen3.5 35B-A3B Instruct (21 GB), Qwen3 32B (22 GB), Laguna XS 2.1 (22 GB), Nanbeige4.3 33B (22 GB), Granite Switch 4.1 30B (23 GB), Gemma 2 27B Instruct (23 GB), Gemma 3 27B Instruct (23 GB), Ornith 1.0 35B (23 GB), Sage-A1.5 (23 GB), Qwen3.6-35B-A3B (24 GB) and more.

Questions

What is the best AI model for the M5 (32 GB, 10-core GPU)?

Qwen3-Coder-30B-A3B at Q4_K_M: the largest model on our shortlist of current models that runs at 4-bit or better at a usable speed (about 37 tok/s, ModelFit est.).

How much memory can a model use on the M5 (32 GB, 10-core GPU)?

About 21 GB of the 32 GB.

How fast is the M5 (32 GB, 10-core GPU) for local LLMs?

Decode speed is limited by memory bandwidth: 153 GB/s. A model that reads 10 GB per token runs at under 15 tokens per second.