gemma4:12b-mlx

THINKING MODEL

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 24, 2026 · Submitted by AAA
Top 61% Compare
Global Score
71 /100
Not Rec.
Hardware Fit
76/100
Quality
69/100

Get this model

Hardware

Machine
MacBook Pro
CPU
Apple M1 Pro
Cores
10 total (8 perf + 2 eff)
Frequency
2.4 GHz
RAM
16 GB LPDDR5
GPU
Apple M1 Pro
OS
macOS 26.6.2
Arch
arm64
Power Mode
balanced

Performance

Tokens/sec
25.0
Standard deviation
±1.6
First chunk latency
787 ms
Time to first token
30.0 s
Load time
4.0 s
Memory usage
7.1 GB (45%)
Total tokens
1460
Thinking tokens (est.)
~723

Score breakdown

Speed
50/50
Time to first token
0/20
Memory
26/30

Quality

Reasoning
14/20
Coding
10/20
Instruction following
9/20
Structured output
15/15
Math
11/15
Multilingual
10/10

Category levels

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

Metadata

Spec version
0.2.1
Runtime
Ollama 0.32.15
Model format
GGUF
Hardware profile
ENTRY
Result hash
8f4a15e7f302d003a373519e92641b38ced64d58f3b4b4ecf84ee63adaf8956e

Interpretation

Hardware fit: 76/100. Overall suitability: NOT RECOMMENDED (Global 71/100). Category profile: Reasoning: Adequate, Coding: Adequate, Instruction Following: Weak, Structured Output: Strong, Math: Adequate, Multilingual: Strong.

Warnings

  • Significant swap activity during benchmark (+0.8 GB). Model may exceed available RAM — results are severely degraded.
  • Running on battery power — performance may be reduced.

Disqualifiers

  • Time to first token too high: 30000ms (maximum: 22068ms for ENTRY profile)

Bench Environment

Power: Battery Swap delta: +0.8 GB CPU load: avg 18% (peak 21%)

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