mistral:7b

llama · 7.2B · Q4_K_M

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 1, 2026

Top 74% Compare

Global Score

61 /100

Good

Hardware Fit

81/100

Quality

48/100

Get this model

🦙

Ollama

ollama pull mistral:7b

View on Ollama Library

ollama.com/library/mistral

🤗

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

Performance

Tokens/sec Tokens generated per second — higher is better: 13.6
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: 517 ms
Load time Time to load the model into memory before inference: 3.0 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

21/40

Time to first token

30/30

Memory

30/30

Quality

Reasoning

8/20

Coding

0/20

Instruction following

12/20

Structured output

14/15

Math

5/15

Multilingual

9/10

Category levels

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

Metadata

Spec version: 0.1.0
Runtime: Ollama 0.17.4
Model format: GGUF
Hardware profile: BALANCED
Result hash: ac7d3dacde866a5eea28c1b37aee9d83fc39b7289285bee117445ca64fff3bf8

Interpretation

Hardware fit: 81/100. Overall suitability: GOOD (Global 61/100). Category profile: Reasoning: Weak, Coding: Poor, Instruction Following: Adequate, Structured Output: Strong, Math: Weak, Multilingual: Strong.

Run yours now

npx metrillm@latest bench

Requires Node 20+ and Ollama running