aya:8b

command-r · 8.0B · F16

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 1, 2026

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Global Score

70 /100

Good

Hardware Fit

92/100

Quality

55/100

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Ollama

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ollama.com/library/aya

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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: 20.0
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.3
Time to first token How fast the model starts responding — lower is better: 300 ms
Load time Time to load the model into memory before inference: 0.9 s
Memory usage RAM consumed during inference — percentage of total system memory: 6.0 GB (19%)
Total tokens Total number of tokens generated across all benchmark prompts: 1020

Score breakdown

Speed

32/40

Time to first token

30/30

Memory

30/30

Quality

Reasoning

10/20

Coding

6/20

Instruction following

13/20

Structured output

15/15

Math

2/15

Multilingual

9/10

Category levels

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

Metadata

Spec version: 0.2.0
Runtime: Ollama 0.17.4
Model format: GGUF
Hardware profile: BALANCED
Result hash: 29abb61fcc14a9a83fafb5159408ae72c06c68580da04f5d21a925d4ddb5acfc

Interpretation

Hardware fit: 92/100. Overall suitability: GOOD (Global 70/100). Category profile: Reasoning: Adequate, Coding: Weak, Instruction Following: Adequate, Structured Output: Strong, Math: Poor, Multilingual: Strong.

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