qwen3.5:9b

qwen35 · 9.7B · Q4_K_M

System manufacturer (AMD Ryzen 5 5500)

16 GB · Microsoft Windows 11 IoT Enterprise LTSC 10.0.26100

Tested on March 7, 2026 · Submitted by Yuuki

Top 42% Compare

Global Score

71 /100

Good

Hardware Fit

56/100

Quality

78/100

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ollama pull qwen3.5:9b

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ollama.com/library/qwen3.5

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GGUF versions & quantizations

Hardware

Machine: System manufacturer
CPU: AMD Ryzen 5 5500
Cores: 12 total (12 perf)
Frequency: 4.2 GHz
RAM: 16 GB DDR4
GPU: NVIDIA GeForce RTX 3060
OS: Microsoft Windows 11 IoT Enterprise LTSC 10.0.26100
Arch: x64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 5.3
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.0
First chunk latency Delay before the first streamed chunk arrives from runtime: 1.6 s
Time to first token How fast the model starts responding — lower is better: 1.6 s
Load time Time to load the model into memory before inference: 4.0 s
Memory usage RAM consumed during inference — percentage of total system memory: 7.9 GB (50%)
Total tokens Total number of tokens generated across all benchmark prompts: 1018

Score breakdown

Speed

11/50

Time to first token

20/20

Memory

25/30

Quality

Reasoning

14/20

Coding

17/20

Instruction following

12/20

Structured output

15/15

Math

10/15

Multilingual

10/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.17.7
Model format: GGUF
Hardware profile: ENTRY
Result hash: 92ec6d036582be1904c4f4ae76b9173e83243011b3a67c137a49037fd4fc85e6

Interpretation

Hardware fit: 56/100. Overall suitability: GOOD (Global 71/100). Category profile: Reasoning: Adequate, Coding: Strong, Instruction Following: Adequate, Structured Output: Strong, Math: Adequate, Multilingual: Strong.

Bench Environment

CPU load: avg 48% (peak 59%)

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