The M2 Max for local AI.

The M2 Max has up to 96 GB of unified memory, read at up to 400 GB/s. Here's what that means for running language models on a Mac with it, worked out from Apple's own figures.

1The specs that matter for AI

Unified memory96 GB
Memory bandwidth400 GB/s
Found in14- and 16-inch MacBook Pro (2023), Mac Studio (2023)
Dedicated seat for itPro seat: mines up to 80 MLX a day

2Which models fit

At 4 bits per weight a model needs a little over half a gigabyte per billion parameters, plus room for its context and macOS. With 96 GB, the M2 Max comfortably holds models up to about 128 billion parameters.

Model at 4-bitMemory it needsFits on the M2 Max
8B model4.5 GBYes
14B model7.9 GBYes
32B model18 GBYes
70B model39.4 GBYes
gpt-oss-120b, mixture-of-experts65 GBYes
Qwen3.5-397B-A17B, mixture-of-experts223.3 GBNo
DeepSeek-V4.1-Flash, mixture-of-experts316 GBNo

3How fast it runs

Writing text is limited by memory bandwidth: every new token reads the model's active weights once. Dividing the M2 Max's 400 GB/s by the bytes read per token gives the ceiling below. Real runs usually reach about 45% to 80% of it (llama.cpp benchmarks).

Model at 4-bitRead per tokenCeiling for one chat
8B model4.5 GB89 tokens/s
14B model7.9 GB51 tokens/s
32B model18 GB22 tokens/s
70B model39.4 GB10 tokens/s
gpt-oss-120b, mixture-of-experts2.7 GB148 tokens/s

5Compare with other chips

6Questions

Can the M2 Max run a 70B model?
Yes. A 70B model at 4-bit needs about 40 GB, and the M2 Max has up to 96 GB. Expect a ceiling of about 10 tokens a second for one chat.
How many tokens per second does the M2 Max get?
For an 8B model at 4-bit, the ceiling is about 89 tokens a second, and real runs reach roughly half to four fifths of it. Bigger models are proportionally slower.
Is the M2 Max good for AI?
For running models locally, memory and bandwidth matter most. The M2 Max has up to 96 GB at 400 GB/s, enough for models up to about 128 billion parameters. It can also earn by running AI work for MLX Network with MLX Node.

Sources

  1. Apple: M2 Pro and M2 Maxapple.com
  2. llama.cpp: Apple Silicon benchmarksgithub.com
M2 Max for local LLMs: memory, speed and what fits | MLX