qwen3.5:9b

qwen35 · 9.7B · Q4_K_M

THINKING MODEL

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 22, 2026

Top 82% Compare

Global Score

58 /100

Marginal

Hardware Fit

79/100

Quality

49/100

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Ollama

ollama pull qwen3.5:9b

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ollama.com/library/qwen3.5

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GGUF versions & quantizations

Hardware

Machine: MacBook Pro
CPU: Apple M1 Pro
Cores: 10 total (8 perf + 2 eff)
Frequency: 2.4 GHz
RAM: 16 GB LPDDR5
GPU: Apple M1 Pro
OS: macOS 26.6.2
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 22.1
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: 601 ms
Time to first token How fast the model starts responding — lower is better: 9.1 s
Load time Time to load the model into memory before inference: 4.2 s
Memory usage RAM consumed during inference — percentage of total system memory: 7.2 GB (45%)
Total tokens Total number of tokens generated across all benchmark prompts: 1429
Thinking tokens (est.) Estimated internal reasoning tokens — models with "thinking" generate more tokens: ~700

Score breakdown

Speed

48/50

Time to first token

5/20

Memory

26/30

Quality

Reasoning

15/20

Coding

4/20

Instruction following

5/20

Structured output

6/15

Math

11/15

Multilingual

8/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.32.14
Model format: GGUF
Hardware profile: ENTRY
Result hash: f830d7342f1d6b7a8d81c33036138ef5ab3309d0e4b8bb763f076a5c3f32f177

Interpretation

Hardware fit: 79/100. Overall suitability: MARGINAL (Global 58/100). Category profile: Reasoning: Adequate, Coding: Poor, Instruction Following: Weak, Structured Output: Weak, Math: Adequate, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 19% (peak 23%)

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