Run Gemma 3 12B on M4 Pro

Yes — Gemma 3 12B (12B) runs at 52 tok/s on M4 Pro with 24 GB RAM using Q4_K_M quantization via MLX. First token latency is 0.7s. Google's 12B model offering strong reasoning for mid-range Macs.

Speed

tok/s

First Token

0.7

seconds

RAM Needed

GB minimum

Engine

MLX

recommended

Benchmark Details

LLMCheck measured Gemma 3 12B on M4 Pro 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	52 tok/s
Time to first token	0.7s
Quantization	Q4_K_M
Minimum RAM	24 GB
Recommended engine	MLX
Parameters	12B
Benchmark date	2026-02

Q4_K_M 12B MLX M4 Pro

Setup Guide: Run Gemma 3 12B on M4 Pro

The recommended engine for Gemma 3 12B on M4 Pro is MLX. Install with pip and pull the model:

pip install mlx-lm

mlx_lm.generate --model mlx-community/gemma-3-12b-q4_k_m --prompt "Hello!"

Alternatively, you can use Ollama for a simpler setup:

ollama run gemma3:12b

Performance on Other Apple Silicon Chips

Chip	Speed	First Token	Min RAM	Engine
M5 Max	68 tok/s	0.6s	64 GB	Ollama
M3	38 tok/s	1.1s	16 GB	Ollama
M2	32 tok/s	1.3s	16 GB	Ollama

System Requirements

To run Gemma 3 12B on M4 Pro you need:

• Mac with M4 Pro chip (or newer)
• 24 GB unified memory minimum
• macOS 13 Ventura or later
• ~20-24 GB free disk space for the model file
• MLX installed (see our Ollama install guide)

Compare More Models

See how Gemma 3 12B stacks up against other models on your specific Mac hardware.

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