orca-mini:7b

llama · 7B · Q4_0

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 1, 2026

Top 74% Compare

Global Score

61 /100

Good

Hardware Fit

98/100

Quality

37/100

Get this model

🦙

Ollama

ollama pull orca-mini:7b

View on Ollama Library

ollama.com/library/orca-mini

🤗

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: 24.4
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: 219 ms
Load time Time to load the model into memory before inference: 0.4 s
Memory usage RAM consumed during inference — percentage of total system memory: 5.8 GB (18%)
Total tokens Total number of tokens generated across all benchmark prompts: 1224

Score breakdown

Speed

38/40

Time to first token

30/30

Memory

30/30

Quality

Reasoning

8/20

Coding

1/20

Instruction following

8/20

Structured output

10/15

Math

2/15

Multilingual

8/10

Category levels

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

Metadata

Spec version: 0.2.0
Runtime: Ollama 0.17.4
Model format: GGUF
Hardware profile: BALANCED
Result hash: 0a637a484a4b97aef3343332b8d404374a796b5baacf8dc8cc3732977cf326a4

Interpretation

Hardware fit: 98/100. Overall suitability: GOOD (Global 61/100). Category profile: Reasoning: Weak, Coding: Poor, Instruction Following: Weak, Structured Output: Adequate, Math: Poor, Multilingual: Strong.

Run yours now

npx metrillm@latest bench

Requires Node 20+ and Ollama running