starling-lm:7b

llama · 7B · Q4_0

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 6, 2026

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Global Score

65 /100

Good

Hardware Fit

96/100

Quality

52/100

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ollama pull starling-lm:7b

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ollama.com/library/starling-lm

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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: 23.8
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.0
First chunk latency Delay before the first streamed chunk arrives from runtime: 232 ms
Time to first token How fast the model starts responding — lower is better: 232 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: 5.3 GB (17%)
Total tokens Total number of tokens generated across all benchmark prompts: 1387

Score breakdown

Speed

46/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

10/20

Coding

13/20

Instruction following

8/20

Structured output

3/15

Math

9/15

Multilingual

9/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.17.6
Model format: GGUF
Hardware profile: BALANCED
Result hash: e555a76d47197dd213a1a4a04f70a36d7647ffd99d50c0e4593c272dfecb7ba5

Interpretation

Hardware fit: 96/100. Overall suitability: GOOD (Global 65/100). Category profile: Reasoning: Adequate, Coding: Adequate, Instruction Following: Weak, Structured Output: Poor, Math: Adequate, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 4% (peak 11%)

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$ metrillm

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Or run without installing: npx metrillm@latest