gemma4:12b-mlx

MacBook Pro (Apple M2 Pro)

16 GB · macOS 26.5

Tested on July 4, 2026 · Submitted by enigmatracer

Top 5% Compare

Global Score

91 /100

Excellent

Hardware Fit

96/100

Quality

89/100

Get this model

Get it in LM Studio

Search and download models directly from the app

🤗

Find on HuggingFace

MLX versions & conversions

Hardware

Machine: MacBook Pro
CPU: Apple M2 Pro
Cores: 10 total (6 perf + 4 eff)
Frequency: 2.4 GHz
RAM: 16 GB LPDDR5
GPU: Apple M2 Pro
OS: macOS 26.5
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 24.7
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±1.8
First chunk latency Delay before the first streamed chunk arrives from runtime: 610 ms
Time to first token How fast the model starts responding — lower is better: 610 ms
Load time Time to load the model into memory before inference: 3.6 s
Memory usage RAM consumed during inference — percentage of total system memory: 7.1 GB (45%)
Total tokens Total number of tokens generated across all benchmark prompts: 1107

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

26/30

Quality

Reasoning

16/20

Coding

19/20

Instruction following

17/20

Structured output

15/15

Math

12/15

Multilingual

10/10

Category levels

Reasoning: Strong Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Strong Multilingual: Strong

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.31.1
Model format: GGUF
Hardware profile: ENTRY
Result hash: f0d2f567a86dc7c7b841e8858bfb73908ce88b727e507e11177bb4988890cb1b

Interpretation

Hardware fit: 96/100. Overall suitability: EXCELLENT (Global 91/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Strong, Structured Output: Strong, Math: Strong, Multilingual: Strong.

Warnings

Significant swap activity during benchmark (+1.0 GB). Model may exceed available RAM — results are severely degraded.

Bench Environment

Power: AC Swap delta: +1.0 GB CPU load: avg 12% (peak 24%)

Run yours now

$ npm install -g metrillm@latest

$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest