Run Gemma 4 31B on M4 Max

Yes — Gemma 4 31B (31B) runs at 18 tok/s on M4 Max with 48 GB RAM using Q4_K_M quantization via MLX. First token latency is 1.1s. Google's flagship 31B dense model, Arena AI #3 among open models.

Speed

tok/s

First Token

1.1

seconds

RAM Needed

GB minimum

Engine

MLX

recommended

Benchmark Details

LLMCheck measured Gemma 4 31B on M4 Max using the standard methodology: Q4_K_M quantization, 256-token input, 512-token output, 3 runs averaged on a freshly-booted system.

Metric	Value
Tokens per second	18 tok/s
Time to first token	1.1s
Quantization	Q4_K_M
Minimum RAM	48 GB
Recommended engine	MLX
Parameters	31B
Benchmark date	2026-04

Q4_K_M 31B MLX M4 Max

Setup Guide: Run Gemma 4 31B on M4 Max

The recommended engine for Gemma 4 31B on M4 Max is MLX. Install with pip and pull the model:

pip install mlx-lm

mlx_lm.generate --model mlx-community/gemma-4-31b-q4_k_m --prompt "Hello!"

Alternatively, you can use Ollama for a simpler setup:

ollama run gemma4:31b

Performance on Other Apple Silicon Chips

Chip	Speed	First Token	Min RAM	Engine
M5 Max	26 tok/s	0.7s	128 GB	MLX
M5 Max	22 tok/s	0.9s	64 GB	Ollama
M4 Pro	14 tok/s	1.4s	24 GB	Ollama

System Requirements

To run Gemma 4 31B on M4 Max you need:

• Mac with M4 Max chip (or newer)
• 48 GB unified memory minimum
• macOS 13 Ventura or later
• ~40-48 GB free disk space for the model file
• MLX installed (see our Ollama install guide)

Compare More Models

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