Device profile · macOS

Best local LLMs for Apple M5 (32GB)

Apple M5 (32GB) has ~21 GB estimated usable for weights, cache and runtime; 109 of 161 tracked models fit at the estimated 4K baseline. Best tool: LM Studio.

96 fit with room 13 tight fit 52 too heavy

Usable memory: ~21 GB
Estimated fits: 109
Too large: 52
Suggested fit: 27B

Suggested fit Q4_K_M

Gemma 3 27B Yes

Runs at Q4_K_M using ~18.6 GB of ~21 GB usable.

The suggested model uses recorded Arena scores where available, then estimated fit and speed. Score coverage is partial; it does not establish the best model for every task. Fit is an estimate, not a benchmark on this device.

Set up Gemma 3 27B on this device →

Estimated memory fits on Apple M5 (32GB)

Compatible models 109 total

Too large for this device

Best way to run models on macOS

Runtime guide macOS

Beginner: LM Studio, Polished GUI, ships MLX on Apple Silicon, one-click model downloads.

Power user: mlx-lm, Apple's MLX framework, usually the fastest on Apple Silicon for the same quant.

vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.

Full macOS tool guide →

FAQ

What is the best local LLM for Apple M5 (32GB)?

Gemma 3 27B is a suggested fit, using ~18.6 GB at Q4_K_M of the ~21 GB usable on Apple M5 (32GB).

How much of Apple M5 (32GB)'s memory can I use for a model?

About 21 GB. Apple Silicon shares one unified memory pool; roughly 66-75% is available to the GPU for model weights, the rest is reserved for macOS.

Which tool should I use on macOS?

LM Studio (Polished GUI, ships MLX on Apple Silicon, one-click model downloads.) or mlx-lm for speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.