deepscaler:1.5b

qwen2 · 1.8B · F16

THINKING MODEL

Microsoft WSL (AMD Ryzen 5 5500)

8 GB · Ubuntu 26.04.1 LTS

Tested on October 11, 2026

Top 75% Compare

Global Score

64 /100

Good

Hardware Fit

98/100

Quality

49/100

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Ollama

ollama pull deepscaler:1.5b

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ollama.com/library/deepscaler

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GGUF versions & quantizations

Hardware

Machine: Microsoft WSL
CPU: AMD Ryzen 5 5500
Cores: 12 threads (6 cores)
RAM: 8 GB
GPU: Integrated / Unknown
OS: Ubuntu 26.04.1 LTS
Arch: x64

Performance

Tokens/sec Tokens generated per second — higher is better: 104.6
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±1.4
First chunk latency Delay before the first streamed chunk arrives from runtime: 849 ms
Time to first token How fast the model starts responding — lower is better: 850 ms
Load time Time to load the model into memory before inference: 10.5 s
Memory usage RAM consumed during inference — percentage of total system memory: 3.0 GB (40%)
Total tokens Total number of tokens generated across all benchmark prompts: 1394

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

28/30

Quality

Reasoning

10/20

Coding

6/20

Instruction following

10/20

Structured output

7/15

Math

11/15

Multilingual

5/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.34.0
Model format: GGUF
Hardware profile: ENTRY
Result hash: f732045bf6a19db54c373731f621752efcdf11718024ebe57ada3787b3eadb1b

Interpretation

Hardware fit: 98/100. Overall suitability: GOOD (Global 64/100). Category profile: Reasoning: Adequate, Coding: Weak, Instruction Following: Adequate, Structured Output: Weak, Math: Adequate, Multilingual: Weak.

Bench Environment

CPU load: avg 28% (peak 30%)

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$ metrillm

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Or run without installing: npx metrillm@latest