Can the M1 Max run a 70B model?

Yes. A 70B model at 4-bit needs about 40 GB, and the M1 Max has up to 64 GB. Expect a ceiling of about 10 tokens a second for one chat.

How many tokens per second does the M1 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 M1 Max good for AI?

For running models locally, memory and bandwidth matter most. The M1 Max has up to 64 GB at 400 GB/s, enough for models up to about 85 billion parameters. It can also earn by running AI work for MLX Network with MLX Node.

M1 Max for local LLMs: memory, speed and what fits

1The specs that matter for AI

Unified memory	64 GB
Memory bandwidth	400 GB/s
Found in	14- and 16-inch MacBook Pro (2021), Mac Studio (2022)
Dedicated seat for it	Pro 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 64 GB, the M1 Max comfortably holds models up to about 85 billion parameters.

Model at 4-bit	Memory it needs	Fits on the M1 Max
8B model	4.5 GB	Yes
14B model	7.9 GB	Yes
32B model	18 GB	Yes
70B model	39.4 GB	Yes
gpt-oss-120b, mixture-of-experts	65 GB	No
Qwen3.5-397B-A17B, mixture-of-experts	223.3 GB	No
DeepSeek-V4.1-Flash, mixture-of-experts	316 GB	No

3How fast it runs

Writing text is limited by memory bandwidth: every new token reads the model's active weights once. Dividing the M1 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-bit	Read per token	Ceiling for one chat
8B model	4.5 GB	89 tokens/s
14B model	7.9 GB	51 tokens/s
32B model	18 GB	22 tokens/s
70B model	39.4 GB	10 tokens/s

5Compare with other chips

6Questions

Can the M1 Max run a 70B model?: Yes. A 70B model at 4-bit needs about 40 GB, and the M1 Max has up to 64 GB. Expect a ceiling of about 10 tokens a second for one chat.
How many tokens per second does the M1 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 M1 Max good for AI?: For running models locally, memory and bandwidth matter most. The M1 Max has up to 64 GB at 400 GB/s, enough for models up to about 85 billion parameters. It can also earn by running AI work for MLX Network with MLX Node.

Sources

Apple: M1 Pro and M1 Maxapple.com
llama.cpp: Apple Silicon benchmarksgithub.com