llama3.2:latest

llama · 3.2B · Q4_K_M

Mac Mini (Apple M4 Pro)

64 GB · macOS 15.7.4

Tested on February 28, 2026

Top 13% Compare

Global Score

77 /100

Good

Hardware Fit

100/100

Quality

61/100

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Ollama

ollama pull llama3.2:latest

View on Ollama Library

ollama.com/library/llama3.2

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Find on HuggingFace

GGUF versions & quantizations

Hardware

Machine: Mac Mini
CPU: Apple M4 Pro
Cores: 14 total (10 perf + 4 eff)
Frequency: 2.4 GHz
RAM: 64 GB LPDDR5
GPU: Apple M4 Pro
OS: macOS 15.7.4
Arch: arm64

Performance

Tokens/sec Tokens generated per second — higher is better: 98.9
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: 125 ms
Load time Time to load the model into memory before inference: 2.3 s
Memory usage RAM consumed during inference — percentage of total system memory: 22.1 GB (35%)
Total tokens Total number of tokens generated across all benchmark prompts: 1112

Score breakdown

Speed

40/40

Time to first token

30/30

Memory

30/30

Quality

Reasoning

11/20

Coding

14/20

Instruction following

12/20

Structured output

12/15

Math

3/15

Multilingual

9/10

Category levels

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

Metadata

Spec version: 0.1.0
Runtime: Ollama 0.17.4
Model format: GGUF
Hardware profile: HIGH-END
Result hash: 40f1f574f63053019ada56d61392288f4a9ad33adafd324c05bd80a4713be64f

Interpretation

Hardware fit: 100/100. Overall suitability: GOOD (Global 77/100). Category profile: Reasoning: Adequate, Coding: Adequate, Instruction Following: Adequate, Structured Output: Strong, Math: Poor, Multilingual: Strong.

Run yours now

npx metrillm@latest bench

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