mlx-community/gemma-3-1b-it-8bit

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 5, 2026

Top 39% Compare

Global Score

72 /100

Good

Hardware Fit

99/100

Quality

61/100

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Hardware

Machine: MacBook Air
CPU: Apple M4
Cores: 10 total (4 perf + 6 eff)
Frequency: 2.4 GHz
RAM: 32 GB LPDDR5
GPU: Apple M4
OS: macOS 26.3
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 86.3
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±7.9
First chunk latency Delay before the first streamed chunk arrives from runtime: 253 ms
Time to first token How fast the model starts responding — lower is better: 253 ms
Load time Time to load the model into memory before inference: N/A
Memory usage RAM consumed during inference — percentage of total system memory: 1.1 GB (4%)
Total tokens Total number of tokens generated across all benchmark prompts: 1104

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

29/30

Quality

Reasoning

7/20

Coding

14/20

Instruction following

16/20

Structured output

14/15

Math

2/15

Multilingual

8/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: LM Studio 0.4.6+1
Model format: GGUF
Hardware profile: BALANCED
Result hash: a395928b5ffb9dc3762ef503c3f79bfbad315adc24cc8b2ea05549fc19f7a81c

Interpretation

Hardware fit: 99/100. Overall suitability: GOOD (Global 72/100). Category profile: Reasoning: Weak, Coding: Adequate, Instruction Following: Strong, Structured Output: Strong, Math: Poor, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 22% (peak 25%)

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Or run without installing: npx metrillm@latest