qwen3.5:9b

qwen35 · 9.7B · Q4_K_M

THINKING MODEL

MacBook Pro (Apple M1 Max)

32 GB · macOS 26.3

Tested on March 5, 2026 · Submitted by alph0x

Top 78% Compare

Global Score

53 /100

Marginal

Hardware Fit

72/100

Quality

45/100

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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: MacBook Pro
CPU: Apple M1 Max
Cores: 10 total (8 perf + 2 eff)
Frequency: 2.4 GHz
RAM: 32 GB LPDDR5
GPU: Apple M1 Max
OS: macOS 26.3
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 18.6
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.6
First chunk latency Delay before the first streamed chunk arrives from runtime: 403 ms
Time to first token How fast the model starts responding — lower is better: 10.2 s
Load time Time to load the model into memory before inference: 4.3 s
Memory usage RAM consumed during inference — percentage of total system memory: 9.1 GB (28%)
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

38/50

Time to first token

4/20

Memory

30/30

Quality

Reasoning

12/20

Coding

3/20

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 0.17.6
Model format: GGUF
Hardware profile: BALANCED
Result hash: bb04363d493fcbc15da0ea6e8e61d328e532e92aff78d716bd229737ca52eb40

Interpretation

Hardware fit: 72/100. Overall suitability: MARGINAL (Global 53/100). Category profile: Reasoning: Adequate, Coding: Poor, Instruction Following: Weak, Structured Output: Weak, Math: Adequate, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 25% (peak 28%)

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