qwen2.5-coder:3b

qwen2 · 3.1B · Q4_K_M

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 49% Compare

Global Score

73 /100

Good

Hardware Fit

100/100

Quality

61/100

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Ollama

ollama pull qwen2.5-coder:3b

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ollama.com/library/qwen2.5-coder

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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: 1.04 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: 21.3
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.3
First chunk latency Delay before the first streamed chunk arrives from runtime: 969 ms
Time to first token How fast the model starts responding — lower is better: 969 ms
Load time Time to load the model into memory before inference: 6.6 s
Memory usage RAM consumed during inference — percentage of total system memory: 2.0 GB (27%)
Total tokens Total number of tokens generated across all benchmark prompts: 968

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

8/20

Coding

15/20

Instruction following

11/20

Structured output

14/15

Math

4/15

Multilingual

9/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.30.10
Model format: GGUF
Hardware profile: ENTRY
Result hash: 5797de9770d50810d66670b50e1ba91b39985dd40f9371e5d52c689256c51f8b

Interpretation

Hardware fit: 100/100. Overall suitability: GOOD (Global 73/100). Category profile: Reasoning: Weak, Coding: Adequate, Instruction Following: Adequate, Structured Output: Strong, Math: Weak, Multilingual: Strong.

Bench Environment

Thermal: nominal CPU load: avg 6% (peak 11%)

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