smollm2:360m

llama · 361.82M · F16

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 2, 2026

Top 80% Compare

Global Score

59 /100

Marginal

Hardware Fit

100/100

Quality

32/100

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Ollama

ollama pull smollm2:360m

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ollama.com/library/smollm2

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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: 117.9
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.8
Time to first token How fast the model starts responding — lower is better: 43 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: 1.2 GB (4%)
Total tokens Total number of tokens generated across all benchmark prompts: 941

Score breakdown

Speed

40/40

Time to first token

30/30

Memory

30/30

Quality

Reasoning

4/20

Coding

2/20

Instruction following

10/20

Structured output

9/15

Math

4/15

Multilingual

3/10

Category levels

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

Metadata

Spec version: 0.2.0
Runtime: Ollama 0.17.4
Model format: GGUF
Hardware profile: BALANCED
Result hash: d856bd8c414821334c5f79001fe73289d7e67697f32ce9e6c28385c169efe10b

Interpretation

Hardware fit: 100/100. Overall suitability: MARGINAL (Global 59/100). Category profile: Reasoning: Poor, Coding: Poor, Instruction Following: Adequate, Structured Output: Adequate, Math: Poor, Multilingual: Weak.

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