Device profile · macOS

Best local LLMs for Apple M5 (32GB)

Apple M5 (32GB) has ~21 GB usable for model weights and runs 52 of 67 popular models. Best tool: LM Studio.

Usable memory: ~21 GB
Models run: 52
Too large: 15
Top pick: 32B

Top pick Q4_K_M

Qwen2.5 Coder 32B Tight

Fits at Q4_K_M (~20.7 GB of ~21 GB usable) but with little headroom, close other apps.

Runs on Apple M5 (32GB)

Compatible models 52 total

Too large for this device

DeepSeek R1 DeepSeek V3 Qwen3 235B A22B gpt-oss 120B Llama 4 Scout Sarvam-105B Qwen2.5 72B Llama 3.3 70B Mixtral 8x7B Command R 35B Yi 1.5 34B Qwen2.5 32B Qwen3 32B DeepSeek-R1-Distill-Qwen 32B Sarvam-30B

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)?

Qwen2.5 Coder 32B is the strongest model that runs comfortably, using ~20.7 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.

Sources

Memory figures are estimates. See methodology.