gemma-4-31b-it-mlx

gemma4 · 31B · 8bit

MacBook Pro (Apple M4 Max)

128 GB · macOS 26.5.2

Tested on August 19, 2026 · Submitted by Jujube

Top 23% Compare

Global Score

85 /100

Excellent

Hardware Fit

64/100

Quality

94/100

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Hardware

Machine: MacBook Pro
CPU: Apple M4 Max
Cores: 16 total (12 perf + 4 eff)
Frequency: 2.4 GHz
RAM: 128 GB LPDDR5
GPU: Apple M4 Max
OS: macOS 26.5.2
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 13.6
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.4
First chunk latency Delay before the first streamed chunk arrives from runtime: 16 ms
Time to first token How fast the model starts responding — lower is better: 558 ms
Load time Time to load the model into memory before inference: 12.3 s
Memory usage RAM consumed during inference — percentage of total system memory: 0.0 GB (0%)
Total tokens Total number of tokens generated across all benchmark prompts: 1419

Score breakdown

Speed

14/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

19/20

Coding

19/20

Instruction following

18/20

Structured output

15/15

Math

14/15

Multilingual

9/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: LM Studio 0.4.12+1
Model format: MLX
Hardware profile: HIGH-END
Result hash: 8073aad67947f81f6040cb63e0cde27dac32107bf6947c9af5dbea2f0a1b5744

Interpretation

Hardware fit: 64/100. Overall suitability: EXCELLENT (Global 85/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Strong, Structured Output: Strong, Math: Strong, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 8% (peak 8%)

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