llama3.2:1b

llama · 1.2B · Q8_0

Apple M4

32 GB · macOS 26.3

Tested on March 1, 2026

Top 68% Compare

Global Score

63 /100

Good

Hardware Fit

100/100

Quality

39/100

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Ollama

ollama pull llama3.2:1b

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ollama.com/library/llama3.2

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GGUF versions & quantizations

Hardware

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: 28.2
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±1.6
Time to first token How fast the model starts responding — lower is better: 199 ms
Load time Time to load the model into memory before inference: 1.8 s
Memory usage RAM consumed during inference — percentage of total system memory: 4.3 GB (13%)
Total tokens Total number of tokens generated across all benchmark prompts: 1070

Score breakdown

Speed

40/40

Time to first token

30/30

Memory

30/30

Quality

Reasoning

4/20

Coding

0/20

Instruction following

14/20

Structured output

13/15

Math

1/15

Multilingual

7/10

Category levels

Reasoning: Poor Coding: Poor 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: c657f3dc2a1052ad2543ad1262dc6e6eb0660f97fca7a5ef15ae1628a6f8e68f

Interpretation

Hardware fit: 100/100. Overall suitability: GOOD (Global 63/100). Category profile: Reasoning: Poor, Coding: Poor, Instruction Following: Adequate, Structured Output: Strong, Math: Poor, Multilingual: Adequate.

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