google/gemma-3-4b

gemma3 · 4B · 4bit

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 3, 2026 · Submitted by Topaz750

Top 29% Compare

Global Score

76 /100

Good

Hardware Fit

100/100

Quality

66/100

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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: 39.4
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±1.6
First chunk latency Delay before the first streamed chunk arrives from runtime: 468 ms
Time to first token How fast the model starts responding — lower is better: 468 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: 2.8 GB (9%)
Total tokens Total number of tokens generated across all benchmark prompts: 1107

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

10/20

Coding

17/20

Instruction following

13/20

Structured output

12/15

Math

4/15

Multilingual

10/10

Category levels

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

Metadata

Spec version: 0.2.0
Runtime: LM Studio 0.4.6+1
Model format: MLX
Hardware profile: BALANCED
Result hash: cb17c160a11b390191de0c9ff0bf4c3f0fd5a2319888c22e97c31b5ebcce8894

Interpretation

Hardware fit: 100/100. Overall suitability: GOOD (Global 76/100). Category profile: Reasoning: Adequate, Coding: Strong, Instruction Following: Adequate, Structured Output: Strong, Math: Weak, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 30% (peak 45%)

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