VRAMfit guide · updated 2026-06-28
Best Mac for local LLMs
In short: Macs run local LLMs out of their unified memory, so the model "VRAM" is a big slice of system RAM - which is why a Mac Studio with 128-512 GB can hold models that no single consumer GPU can. For local LLMs, buy the most unified memory you can; an Apple Silicon Mac Studio is the simplest way to run 70B+ models on one quiet machine.
What each Mac runs
Unified-memory tiers from the catalog with the biggest model each runs comfortably at Q4_K_M / 8,192 context (usable memory is below the nameplate - the OS reserves some):
| Mac | Usable memory | Bandwidth | Biggest comfortable model |
|---|---|---|---|
| Apple M1 (16GB) | 12 GB usable | 68 GB/s | deepseek-r1:14b (14B) |
| Apple M2 (24GB) | 16 GB usable | 100 GB/s | gpt-oss:20b (20B) |
| Apple M1 Pro (32GB) | 24 GB usable | 200 GB/s | deepseek-r1:32b (32B) |
| Apple M3 Pro (36GB) | 27 GB usable | 150 GB/s | qwen3.5:35b (35B) |
| Apple M1 Max (64GB) | 48 GB usable | 400 GB/s | deepseek-llm:67b (67B) |
| Apple M2 Max (96GB) | 72 GB usable | 400 GB/s | command-r-plus:104b (104B) |
| Apple M1 Ultra (128GB) | 96 GB usable | 800 GB/s | zephyr:141b (141B) |
| Apple M2 Ultra (192GB) | 147 GB usable | 800 GB/s | falcon:180b (180B) |
| Apple M3 Ultra (512GB) | 384 GB usable | 800 GB/s | nemotron-3-ultra (550B) |
Memory vs bandwidth on a Mac
More unified memory lets a Mac hold bigger models; memory bandwidth (higher on Max/Ultra chips) sets how fast they decode. A high-memory but lower-bandwidth Mac can load a huge model yet generate slowly, so for large models prefer the Max/Ultra tiers.
The pick
A Mac Studio with an Ultra chip is the recommended buy for serious local LLMs - it pairs large unified memory with high bandwidth and runs 401 catalog models comfortably, up to nemotron-3-ultra. See every machine and what it runs on the AI machines page.
Frequently asked questions
Which Mac is best for local LLMs?
A Mac Studio with an Ultra chip - it has the most unified memory and the highest bandwidth, so it runs the largest models fastest. A MacBook Pro with a Max chip is the best portable option.
How much memory do I need on a Mac for AI?
Treat it like VRAM: ~16 GB runs small models, 36-48 GB runs ~30B, and 128 GB+ runs 70B-class models. Only part of the nameplate memory is usable for the model.
Is a Mac as fast as a GPU for LLMs?
For models that fit a GPU's VRAM, a discrete GPU is usually faster. The Mac's edge is capacity - it holds models far larger than any single consumer GPU can.