Macs

Which AI models run on the M1 Max (32 GB, 24-core GPU)?

The M1 Max (32 GB, 24-core GPU) has 32 GB of memory, about 21 GB of it usable for a model, and 400 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
400 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 · ~69 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

ModelBest buildMemorySpeed
Qwen3-Coder-30B-A3B30.5B MoEQ4_K_M20 GB~69 tok/s ModelFit est.
Nemotron 3 Nano 30B-A3B30B MoEQ4_K_M19.6 GB~121 tok/s our est.
Qwen3.8-27B27.3BQ4_K_M17.9 GB~17 tok/s ModelFit est.
Gemma 4 26B-A4B25.2B MoEQ4_K_M17.4 GB~60 tok/s ModelFit est.
gpt-oss-20b21B MoEMXFP415.1 GB~60 tok/s ModelFit est.
Nemotron Nano 9B v29BFP1619.4 GB~12 tok/s our est.
Qwen3.5 9B Instruct9BQ8_012.0 GB~31 tok/s ModelFit est.
Qwen2.5 7B Instruct7BQ4_K_M6.6 GB~54 tok/s ModelFit est.
Gemma 3 4B Instruct4BQ8_05.0 GB~57 tok/s ModelFit est.
Olmo 3.1 32B Instruct32BQ4_K_M21 GB~14 tok/s ModelFit est.
Cohere North Mini Code30BQ4_K_M20 GBno estimate
Nemotron 3.5 Lightning 30B-A3B30B MoEIQ4_XS20 GB~116 tok/s our est.
GLM-4.7-Flash 30B-A3B30B MoEQ4_K_M20 GB~64 tok/s ModelFit est.
Muse Glimmer 30B29.8BQ4_K_M18.3 GB~17 tok/s ModelFit est.
Granite 4.2 30B29.3BQ4_K_M17.9 GB~15 tok/s ModelFit est.
AREX-2 27B27.4BQ4_K_M18.6 GB~16 tok/s ModelFit est.
Qwen3.5 27B Instruct27BQ4_K_M17.4 GB~17 tok/s ModelFit est.
Qwen3.6 27B27BQ4_K_M19.4 GB~17 tok/s ModelFit est.
Jebadiah 27B27BQ5_K_M21 GB~15 tok/s ModelFit est.
Mistral Small 3.124BQ4_K_M16.4 GB~15 tok/s our est.
LFM2 24B-A2B Instruct24B MoEQ4_K_M15.3 GB~98 tok/s ModelFit est.
Devstral Small 2 24B24BQ4_K_M16.6 GB~18 tok/s ModelFit est.
Mistral Small 22B22BQ4_K_M18.4 GB~20 tok/s ModelFit est.
Qwen2.5 14B Instruct14BQ4_K_M12.3 GB~28 tok/s ModelFit est.
Phi-3 Medium 14B14BQ4_K_M12.3 GB~20 tok/s our est.
Phi-4 14B14BQ8_015.9 GB~17 tok/s ModelFit est.
Qwen2.5 Coder 14B14BQ4_K_M12.3 GB~28 tok/s ModelFit est.
Qwen3 14B14BQ8_017.3 GB~17 tok/s ModelFit est.
DeepSeek-R1 Distill Qwen 14B14BQ8_016.0 GB~17 tok/s ModelFit est.
Ministral 3 14B13.5BQ4_K_M10.3 GB~28 tok/s ModelFit est.
Mellum2.1 12B-A2.5B Thinking12.1B MoEQ4_K_M9.3 GB~131 tok/s our est.
Mistral Nemo 12B12BQ8_013.4 GB~21 tok/s ModelFit est.
Gemma 3 12B Instruct12BQ4_K_M10.7 GB~33 tok/s ModelFit est.
Gemma 4 12B12BQ8_014.1 GB~20 tok/s ModelFit est.
GLM-4-9B-Chat9.4BQ8_011.2 GB~28 tok/s ModelFit est.
Gemma 2 9B Instruct9BQ4_K_M8.2 GB~36 tok/s ModelFit est.
Ornith 1.0 9B9BQ4_K_M6.7 GB~49 tok/s ModelFit est.
MiMo-V2.6-Distill-Qwen-9B9BQ4_K_M6.9 GB~48 tok/s ModelFit est.
Jebadiah 9B9BQ8_011.0 GB~30 tok/s ModelFit est.
Granite 4.2 8B8.8BQ4_K_M6.1 GB~44 tok/s ModelFit est.
Granite Switch 4.1 8B8.8BQ4_K_M7.6 GB~36 tok/s ModelFit est.
MiniCPM-V 4.5 8B8.7BQ4_K_M6.8 GB~48 tok/s ModelFit est.
Ministral 3 8B8.4BQ4_K_M7.1 GB~41 tok/s ModelFit est.
LFM2.5 8B-A1B8.3B MoEQ4_K_M6.6 GB~123 tok/s ModelFit est.
Llama 3.1 8B Instruct8BQ8_09.2 GB~31 tok/s ModelFit est.
Qwen3 8B8BQ8_09.3 GB~30 tok/s ModelFit est.
Granite 4.1 8B Instruct8BQ4_K_M6.6 GB~42 tok/s ModelFit est.
Mistral 7B Instruct7BQ8_08.4 GB~32 tok/s ModelFit est.
Qwen2.5 Coder 7B7BQ4_K_M6.6 GB~54 tok/s ModelFit est.
DeepSeek-R1 Distill Qwen 7B7BQ8_08.7 GB~34 tok/s ModelFit est.
Gemma 4 E4B4.5BQ8_08.7 GB~50 tok/s ModelFit est.
Qwen3.5 4B Instruct4BQ8_05.4 GB~54 tok/s ModelFit est.
NVIDIA Nemotron 3.5 Bolt E4B4BQ4_K_M9.1 GB~62 tok/s ModelFit est.
Phi-3 Mini 3.8B3.8BQ4_K_M4.3 GB~69 tok/s our est.
Phi-4 Mini 3.8B3.8BQ8_04.9 GB~54 tok/s ModelFit est.
Granite 4.2 3B3.7BQ4_K_M3.2 GB~92 tok/s ModelFit est.
Ministral 3 3B3.4BQ4_K_M4.1 GB~70 tok/s ModelFit est.
Qwen2.5 3B Instruct3BQ4_K_M3.6 GB~104 tok/s ModelFit est.
Llama 3.2 3B Instruct3BQ4_K_M3.6 GB~90 tok/s ModelFit est.
Granite 4.1 3B Instruct3BQ4_K_M3.0 GB~92 tok/s ModelFit est.
Gemma 4 E2B2.3BQ8_05.7 GB~104 tok/s ModelFit est.
Gemma 2 2B Instruct2BQ4_K_M2.8 GB~101 tok/s ModelFit est.
Qwen3.5 2B Instruct2BQ4_K_M2.8 GB~105 tok/s ModelFit est.
LFM3 1.7B1.73BQ4_K_M2.1 GB~159 tok/s ModelFit est.
Qwen2.5 1.5B Instruct1.5BQ4_K_M2.5 GB~163 tok/s ModelFit est.
Llama 3.2 1B Instruct1BQ4_K_M2.0 GB~180 tok/s ModelFit est.
Gemma 3 1B Instruct1BQ8_02.0 GB~164 tok/s ModelFit est.
Qwen3.5 0.8B Instruct0.8BQ4_K_M1.8 GB~190 tok/s ModelFit est.
Qwen2.5 0.5B Instruct0.5BQ4_K_M1.8 GB~263 tok/s ModelFit est.
SmolLM2 360M0.36BQ4_K_M1.5 GB~185 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 M1 Max (32 GB, 24-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 69 tok/s, ModelFit est.).

How much memory can a model use on the M1 Max (32 GB, 24-core GPU)?

About 21 GB of the 32 GB.

How fast is the M1 Max (32 GB, 24-core GPU) for local LLMs?

Decode speed is limited by memory bandwidth: 400 GB/s. A model that reads 10 GB per token runs at under 40 tokens per second.