Run Gemma 4 E4B on M4 Pro

Yes — Gemma 4 E4B (4B) runs at 78 tok/s on M4 Pro with 24 GB RAM using Q4_K_M quantization via MLX. First token latency is 0.3s. Google's 4B PLE model with multimodal capabilities and outstanding speed.

Speed

tok/s

First Token

0.3

seconds

RAM Needed

GB minimum

Engine

MLX

recommended

Benchmark Details

LLMCheck measured Gemma 4 E4B 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	78 tok/s
Time to first token	0.3s
Quantization	Q4_K_M
Minimum RAM	24 GB
Recommended engine	MLX
Parameters	4B
Benchmark date	2026-04

Q4_K_M 4B MLX M4 Pro

Setup Guide: Run Gemma 4 E4B on M4 Pro

The recommended engine for Gemma 4 E4B on M4 Pro is MLX. Install with pip and pull the model:

pip install mlx-lm

mlx_lm.generate --model mlx-community/gemma-4-e4b-q4_k_m --prompt "Hello!"

Alternatively, you can use Ollama for a simpler setup:

ollama run gemma4:e4b

Performance on Other Apple Silicon Chips

Chip	Speed	First Token	Min RAM	Engine
M5 Max	128 tok/s	0.2s	128 GB	MLX
M5 Pro	92 tok/s	0.3s	24 GB	Ollama
M3	62 tok/s	0.4s	16 GB	Ollama
M1	42 tok/s	0.6s	8 GB	Ollama

System Requirements

To run Gemma 4 E4B 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 4 E4B stacks up against other models on your specific Mac hardware.

Open Compare Tool Full Leaderboard