codegemma:7b

gemma · 9B · Q4_0

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 1, 2026

Top 25% Compare

Global Score

74 /100

Good

Hardware Fit

91/100

Quality

62/100

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GGUF versions & quantizations

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: 18.7
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.5
Time to first token How fast the model starts responding — lower is better: 320 ms
Load time Time to load the model into memory before inference: 0.8 s
Memory usage RAM consumed during inference — percentage of total system memory: 8.7 GB (27%)
Total tokens Total number of tokens generated across all benchmark prompts: 900

Score breakdown

Speed

31/40

Time to first token

30/30

Memory

30/30

Quality

Reasoning

1/20

Coding

14/20

Instruction following

13/20

Structured output

15/15

Math

10/15

Multilingual

9/10

Category levels

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

Metadata

Spec version: 0.2.0
Runtime: Ollama 0.17.4
Model format: GGUF
Hardware profile: BALANCED
Result hash: 0ea23e6bf78e899e81cc3e1eef395933e7c424a811649df96f046411d1edf94e

Interpretation

Hardware fit: 91/100. Overall suitability: GOOD (Global 74/100). Category profile: Reasoning: Poor, Coding: Adequate, Instruction Following: Adequate, Structured Output: Strong, Math: Adequate, Multilingual: Strong.

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