llama3.2:1b

llama · 1.2B · Q8_0

NVIDIA NVIDIA Jetson Orin Nano Engineering Reference Developer Kit Super (Cortex-A78AE)

7 GB · Ubuntu 22.04.5 LTS

Tested on June 26, 2026

Top 68% Compare

Global Score

63 /100

Good

Hardware Fit

100/100

Quality

47/100

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ollama pull llama3.2:1b

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GGUF versions & quantizations

Hardware

Machine: NVIDIA NVIDIA Jetson Orin Nano Engineering Reference Developer Kit Super
CPU: Cortex-A78AE
Cores: 6 total (6 perf)
Frequency: 1.11 GHz
RAM: 7 GB
GPU: Integrated / Unknown
OS: Ubuntu 22.04.5 LTS
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 40.2
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.7
First chunk latency Delay before the first streamed chunk arrives from runtime: 1.1 s
Time to first token How fast the model starts responding — lower is better: 1.1 s
Load time Time to load the model into memory before inference: 6.2 s
Memory usage RAM consumed during inference — percentage of total system memory: 1.4 GB (19%)
Total tokens Total number of tokens generated across all benchmark prompts: 1066

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

4/20

Coding

9/20

Instruction following

14/20

Structured output

13/15

Math

1/15

Multilingual

6/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.30.10
Model format: GGUF
Hardware profile: ENTRY
Result hash: 1eb6361a3ad36fa663d0a012bdf55c863ca47edebcb3684729453ec0135e1d11

Interpretation

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

Bench Environment

Thermal: nominal CPU load: avg 7% (peak 11%)

Run yours now

$ npm install -g metrillm@latest

$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest