qwen3.5-9b

qwen35 · 9B · Q4_K_M

THINKING MODEL

Mac mini (Apple M4 Pro)

64 GB · macOS 15.7.4

Tested on March 6, 2026

Top 39% Compare

Global Score

72 /100

Good

Hardware Fit

89/100

Quality

65/100

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Hardware

Machine: Mac mini
CPU: Apple M4 Pro
Cores: 14 total (10 perf + 4 eff)
Frequency: 2.4 GHz
RAM: 64 GB LPDDR5
GPU: Apple M4 Pro
OS: macOS 15.7.4
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 28.9
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.1
First chunk latency Delay before the first streamed chunk arrives from runtime: 338 ms
Time to first token How fast the model starts responding — lower is better: 338 ms
Load time Time to load the model into memory before inference: N/A
Memory usage RAM consumed during inference — percentage of total system memory: 6.1 GB (10%)
Total tokens Total number of tokens generated across all benchmark prompts: 1429

Score breakdown

Speed

39/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

17/20

Coding

15/20

Instruction following

6/20

Structured output

7/15

Math

12/15

Multilingual

8/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: LM Studio 0.4.6+1
Model format: GGUF
Hardware profile: HIGH-END
Result hash: 9a2db0faff08cd3343850e52ea8a5d665e36966fcb947cf38d878d3ec65b311f

Interpretation

Hardware fit: 89/100. Overall suitability: GOOD (Global 72/100). Category profile: Reasoning: Strong, Coding: Adequate, Instruction Following: Weak, Structured Output: Weak, Math: Strong, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 21% (peak 22%)

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