llama3.1:8b

llama · 8.0B · Q4_K_M

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 1, 2026

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Global Score

69 /100

Good

Hardware Fit

93/100

Quality

53/100

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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: 20.2
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.1
Time to first token How fast the model starts responding — lower is better: 481 ms
Load time Time to load the model into memory before inference: 3.4 s
Memory usage RAM consumed during inference — percentage of total system memory: 10.4 GB (33%)
Total tokens Total number of tokens generated across all benchmark prompts: 997

Score breakdown

Speed

33/40

Time to first token

30/30

Memory

30/30

Quality

Reasoning

12/20

Coding

0/20

Instruction following

14/20

Structured output

13/15

Math

4/15

Multilingual

10/10

Category levels

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

Metadata

Spec version: 0.2.0
Runtime: Ollama 0.17.4
Model format: GGUF
Hardware profile: BALANCED
Result hash: 9575d53cbfdc6819b0d7b557b51f7dd4017cddfd0410f0a2be654a4da1f9825c

Interpretation

Hardware fit: 93/100. Overall suitability: GOOD (Global 69/100). Category profile: Reasoning: Adequate, Coding: Poor, Instruction Following: Adequate, Structured Output: Strong, Math: Weak, Multilingual: Strong.

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