qwen3.5:4b

qwen35 · 4.7B · Q4_K_M

THINKING MODEL

MacBook Pro (Apple M1 Pro)

16 GB · macOS 26.6.2

Tested on August 22, 2026

Top 64% Compare

Global Score

69 /100

Good

Hardware Fit

85/100

Quality

62/100

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Ollama

ollama pull qwen3.5:4b

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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: 36.9
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: 474 ms
Time to first token How fast the model starts responding — lower is better: 6.9 s
Load time Time to load the model into memory before inference: 2.9 s
Memory usage RAM consumed during inference — percentage of total system memory: 5.3 GB (33%)
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: ~768

Score breakdown

Speed

50/50

Time to first token

6/20

Memory

29/30

Quality

Reasoning

16/20

Coding

1/20

Instruction following

14/20

Structured output

9/15

Math

12/15

Multilingual

10/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.32.14
Model format: GGUF
Hardware profile: ENTRY
Result hash: e5e78d9d6d40a5293d6fa2ecdc529c0d15945a9338f1cc58a75b87d757d69cbc

Interpretation

Hardware fit: 85/100. Overall suitability: GOOD (Global 69/100). Category profile: Reasoning: Strong, Coding: Poor, Instruction Following: Adequate, Structured Output: Adequate, Math: Strong, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 30% (peak 32%)

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$ metrillm

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