Sat Aug 15 2026 08:00:00 GMT+0800 (中国标准时间)

Run LLMs Locally on a Mac (M1–M5, 2026 Guide)

Unified memory changes the rules: which models fit your Mac's RAM, MLX vs Ollama vs llama.cpp, and how the browser detector reads your Apple Silicon chip.

Run LLMs Locally on a Mac (M1–M5, 2026 Guide)

Apple Silicon is the easiest place to run local models: no driver setup, quiet hardware, and unified memory — the GPU and CPU share one pool, so a 64 GB Mac can load models that need a $5,000+ GPU rig.

What your Mac can actually run

Rule of thumb for unified memory: keep weights under ~60% of RAM for comfortable use (macOS and your apps take the rest):

RAMComfortable model classExample
16 GB4–9B, Q4Qwen3.5 9B Q4_K_M (~5.2 GB)
24–36 GB12–27B, Q4Gemma 4 12B, Bonsai 27B
48–64 GB30–70B, Q4Llama 3.3 70B Q4_K_M (~40 GB)
128 GB+120B+ MoE, Q3–Q4Qwen3.5 122B A10B, DeepSeek V4 Flash

Bandwidth, not compute, sets your speed: an M4 Max (546 GB/s) decodes roughly twice as fast as an M3 Pro. Tokens-per-second ≈ bandwidth ÷ model size per token, and that is the number to compare with PC GPUs.

Pick an engine

EngineBest forNotes
OllamaGetting startedOne command, manages models and server
MLXMac-native performanceApple Silicon first, great for M-series
llama.cppMaximum controlGGUF support everywhere, fine-grained flags

Start with Ollama:

brew install ollama
ollama pull qwen3.5:9b
ollama run qwen3.5:9b

How our detector sees your Mac

Open the homepage tool in Safari or Chrome. The browser reports your chip through WebGPU (GPUAdapterInfo) or WebGL. On older Safari versions WebGL is masked, so if detection fails, pick your Mac from the manual list — the recommendations then use your exact RAM configuration.

Which Mac to buy for AI (2026)

Before buying, run the self-hosting savings calculator against the models you plan to use — a Mac often beats cloud pricing within the first year at 50M+ tokens/month.

Bottom line

Mac local AI is about RAM first, bandwidth second, cores a distant third. Buy memory, then pick the largest model your budget allows — our tool will tell you exactly what fits.

Ready to check your own hardware? Run the GPU detection tool and see which of these models fit, or browse the full model directory.