smollm2:1.7b

llama · 1.7B · Q8_0

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 2, 2026

Top 44% Compare

Global Score

69 /100

Good

Hardware Fit

100/100

Quality

49/100

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ollama pull smollm2:1.7b

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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: 51.8
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.4
Time to first token How fast the model starts responding — lower is better: 84 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: 3.7 GB (12%)
Total tokens Total number of tokens generated across all benchmark prompts: 1215

Score breakdown

Speed

40/40

Time to first token

30/30

Memory

30/30

Quality

Reasoning

7/20

Coding

10/20

Instruction following

12/20

Structured output

13/15

Math

1/15

Multilingual

6/10

Category levels

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

Metadata

Spec version: 0.2.0
Runtime: Ollama 0.17.4
Model format: GGUF
Hardware profile: BALANCED
Result hash: 7e8e2c2dcc8d872a8814de6b32e29051dd5062aa2da2b49cf66d051a25c5cb44

Interpretation

Hardware fit: 100/100. Overall suitability: GOOD (Global 69/100). Category profile: Reasoning: Weak, Coding: Adequate, Instruction Following: Adequate, Structured Output: Strong, Math: Poor, Multilingual: Adequate.

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