Mac Studio with M3 Ultra for local AI.

The M3 Ultra reads memory at 819 GB/s, which sets how fast it writes. Memory decides which models fit, and it can’t be upgraded later, so pick the size here.

96 GB43 models run wellgpt-oss-120b · 137–243 tok/s256 GB53 models run wellMiMo V2.6 Flash · 44–78 tok/s512 GB60 models run wellDeepSeek V4.1 Flash 1017 · 41–73 tok/s

By memory size

MemoryRun wellBiggest that runs wellgpt-oss-20b
96 GB819 GB/s43gpt-oss-120b194–345 tok/s
256 GB819 GB/s53MiMo V2.6 Flash194–345 tok/s
512 GB819 GB/s60DeepSeek V4.1 Flash 1017194–345 tok/s

Models: Mac Studio (2025). Not every memory size is offered with every model; Apple’s Tech Specs list what each one comes with.

Questions

Is the Mac Studio with M3 Ultra good for local LLMs?
With 512 GB it runs 60 of 73 open models well, up to DeepSeek V4.1 Flash 1017, and writes about 194–345 tokens a second with gpt-oss-20b. The M3 Ultra reads memory at 819 GB/s, which sets how fast it writes.
How much memory should a Mac Studio with M3 Ultra have for AI?
With 96 GB it runs 43 open models well; with 512 GB, 60, up to DeepSeek V4.1 Flash 1017. Memory decides which models fit, and it can’t be upgraded later.

Other Macs

The Mac Studio with other chips:

Head to head:

Against PCs and graphics cards:

The M3 Ultra for local AI · The best Mac for local LLMs · Every Mac

How it’s worked out

Memory: the model’s parameters at 8, 6, 4, 3 or 2 bits per weight plus MLX’s group scales (half a bit per weight), or its native format, with room for the context on top. By default macOS lets the GPU use about 75% of unified memory. Speed: memory bandwidth divided by the bytes read per token is the ceiling for one conversation; in llama.cpp’s public Apple Silicon benchmarks real runs reach about 45% to 80% of it, which is the range shown. These are estimates, not measurements: measure your own Mac on MLX Bench. Model figures from each official model card, chip figures from Apple’s Tech Specs. Checked 2026-10-19. Same data as mlx.app/compare.

Mac Studio M3 Ultra for local AI: which LLMs it runs, by memory