mistral:latest

llama · 7.2B · Q4_K_M

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 2, 2026

Top 17% Compare

Global Score

76 /100

Good

Hardware Fit

96/100

Quality

63/100

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Ollama

ollama pull mistral:latest

View on Ollama Library

ollama.com/library/mistral

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Find on HuggingFace

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: 22.5
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.2
Time to first token How fast the model starts responding — lower is better: 257 ms
Load time Time to load the model into memory before inference: 0.6 s
Memory usage RAM consumed during inference — percentage of total system memory: 10.1 GB (32%)
Total tokens Total number of tokens generated across all benchmark prompts: 1182

Score breakdown

Speed

36/40

Time to first token

30/30

Memory

30/30

Quality

Reasoning

8/20

Coding

12/20

Instruction following

15/20

Structured output

14/15

Math

5/15

Multilingual

9/10

Category levels

Reasoning: Weak Coding: Adequate Instruction Following: Strong 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: e722e44e1efa09ead829c843c9575c0e46f186da8285a11099cb0431a6dda6dc

Interpretation

Hardware fit: 96/100. Overall suitability: GOOD (Global 76/100). Category profile: Reasoning: Weak, Coding: Adequate, Instruction Following: Strong, Structured Output: Strong, Math: Weak, Multilingual: Strong.

Run yours now

npx metrillm@latest bench

Requires Node 20+ and Ollama running