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Device profile · macOS

Best local LLMs for Apple M5 (16GB)

Apple M5 (16GB) has ~10.5 GB usable for model weights and runs 39 of 67 popular models. Best tool: LM Studio.

Usable memory
~10.5 GB
Models run
39
Too large
28
Top pick
14B
Top pick Q4_K_M
Qwen2.5 Coder 14B Tight

Fits at Q4_K_M (~10.1 GB of ~10.5 GB usable) but with little headroom, close other apps.

Runs on Apple M5 (16GB)

Compatible models 39 total

Too large for this device

DeepSeek R1DeepSeek V3Qwen3 235B A22Bgpt-oss 120BLlama 4 ScoutSarvam-105BQwen2.5 72BLlama 3.3 70BMixtral 8x7BCommand R 35BYi 1.5 34BQwen2.5 32BQwen3 32BDeepSeek-R1-Distill-Qwen 32BQwen2.5 Coder 32BGranite 4.0 H SmallQwen3 30B-A3BSarvam-30BGemma 2 27BGemma 3 27BMistral Small 3 24BSarvam-M 24Bgpt-oss 20BDeepSeek-V2-LitePhi-4 14BQwen2.5 14BQwen3 14BDeepSeek-R1-Distill-Qwen 14B

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 (16GB)?

Qwen2.5 Coder 14B is the strongest model that runs comfortably, using ~10.1 GB at Q4_K_M of the ~10.5 GB usable on Apple M5 (16GB).

How much of Apple M5 (16GB)'s memory can I use for a model?

About 10.5 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.