qwen2.5-coder:1.5b

qwen2 · 1.5B · Q4_K_M

ECO MODE

LENOVO 20U30029MB (Intel Core™ i5-10210U)

15 GB · Pop 24.04 LTS

Tested on August 28, 2026

Top 65% Compare

Global Score

68 /100

Good

Hardware Fit

100/100

Quality

54/100

Get this model

🦙

Ollama

ollama pull qwen2.5-coder:1.5b

View on Ollama Library

ollama.com/library/qwen2.5-coder

Get it in LM Studio

Search and download models directly from the app

🤗

Find on HuggingFace

GGUF versions & quantizations

Hardware

Machine: LENOVO 20U30029MB
CPU: Intel Core™ i5-10210U
Cores: 8 threads (4 cores)
Frequency: 1.6 GHz
RAM: 15 GB
GPU: CometLake-U GT2 [UHD Graphics]
OS: Pop 24.04 LTS
Arch: x64
Power Mode: low-power

Performance

Tokens/sec Tokens generated per second — higher is better: 21.8
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±1.7
First chunk latency Delay before the first streamed chunk arrives from runtime: 499 ms
Time to first token How fast the model starts responding — lower is better: 499 ms
Load time Time to load the model into memory before inference: 4.4 s
Memory usage RAM consumed during inference — percentage of total system memory: 1.5 GB (10%)
Total tokens Total number of tokens generated across all benchmark prompts: 917

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

8/20

Coding

11/20

Instruction following

13/20

Structured output

11/15

Math

3/15

Multilingual

8/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.32.1
Model format: GGUF
Hardware profile: ENTRY
Result hash: 1fec3bc3c99a2918ee8f336c6fd2e872c4d60e8dfac7083770136d57594a42a2

Interpretation

Hardware fit: 100/100. Overall suitability: GOOD (Global 68/100). Category profile: Reasoning: Weak, Coding: Adequate, Instruction Following: Adequate, Structured Output: Adequate, Math: Poor, Multilingual: Strong.

Warnings

System was in low-power mode during this benchmark.
Running on battery power — performance may be reduced.

Bench Environment

Thermal: nominal Power: Battery CPU load: avg 40% (peak 51%)

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