M2 Max vs M4 Max for local AI.

The M4 Max reads memory about 37% faster than the M2 Max (546 vs 400 GB/s), so it writes about 37% faster with any model that fits both. The M4 Max goes up to 128 GB of memory, the M2 Max to 96 GB.

M2 Max400 GB/sup to 96 GB · 43 models run wellM4 Max410–546 GB/sup to 128 GB · 47 models run well

Side by side

M2 MaxM4 Max
Memory sizes32, 64, 96 GB36, 48, 64, 128 GB
Memory bandwidth400 GB/s410–546 GB/s
For models, at mostabout 72 GBabout 96 GB
Models that run well43 of 7347 of 73
MLX seat classProPro
Found inMacBook Pro (14-inch, 2023), MacBook Pro (16-inch, 2023), Mac Studio (2023)MacBook Pro (14-inch, M4 Pro or M4 Max, 2024), MacBook Pro (16-inch, 2024), Mac Studio (2025)

Speed with popular models

Tokens a second for one conversation, each chip at its largest memory size (96 GB and 128 GB), with the best version of the model that fits.

ModelM2 MaxM4 Max
Llama 3.1 8B Instruct8B21–38 8-bit29–51 8-bit
gpt-oss-20b21B · 3.6B active95–168 native 4.25-bit129–230 native 4.25-bit
Qwen3.6 35B A3B35B · 3B active56–100 8-bit77–137 8-bit
Qwen3.8 27B27B12–21 4-bit11–20 6-bit
Llama 3.3 70B Instruct70B3–6 6-bit3–6 8-bit
gpt-oss-120b117B · 5.1B active67–119 native 4.25-bit91–162 native 4.25-bit
Qwen3.5 122B A10B122B · 10B active41–73 3-bit lower quality44–78 4-bit
DeepSeek V4 Flash 0731284B · 13B activetoo big60–107 2-bit lower quality

Questions

Is the M4 Max faster than the M2 Max for LLMs?
The M4 Max reads memory about 37% faster than the M2 Max (546 vs 400 GB/s), so it writes about 37% faster with any model that fits both. Reading a long prompt depends on GPU compute instead, which this comparison doesn’t cover.
Which can run bigger models, the M2 Max or the M4 Max?
The M4 Max: The M4 Max goes up to 128 GB of memory, the M2 Max to 96 GB. At its largest it runs 47 of 73 open models well, against 43.

More comparisons

The M2 Max for local AI · The M4 Max for local AI · Compare every model · The best Mac for local LLMs

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.

M2 Max vs M4 Max for local LLMs: memory, speed, which to buy