qwen3.5-4b-mlx

qwen3_5 · 4B · 4bit

THINKING MODEL

Mac mini (Apple M4 Pro)

64 GB · macOS 15.7.4

Tested on March 6, 2026

Top 62% Compare

Global Score

62 /100

Not Rec.

Hardware Fit

35/100

Quality

73/100

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MLX versions & conversions

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: 0.0
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: 5.5 s
Time to first token How fast the model starts responding — lower is better: 5.5 s
Load time Time to load the model into memory before inference: N/A
Memory usage RAM consumed during inference — percentage of total system memory: 2.9 GB (5%)
Total tokens Total number of tokens generated across all benchmark prompts: 0

Score breakdown

Speed

0/50

Time to first token

6/20

Memory

29/30

Quality

Reasoning

17/20

Coding

17/20

Instruction following

9/20

Structured output

8/15

Math

13/15

Multilingual

9/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: LM Studio 0.4.6+1
Model format: MLX
Hardware profile: HIGH-END
Result hash: 1551d4fed82fb945f0fda2684b3be3f2c72b6d8c7c4ba59cad6eab7db8d43f95

Interpretation

Hardware fit: 35/100. Overall suitability: NOT RECOMMENDED (Global 62/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Weak, Structured Output: Adequate, Math: Strong, Multilingual: Strong.

Disqualifiers

Token speed too low: 0.0 tok/s (minimum: 5 tok/s for HIGH-END profile)

Bench Environment

Power: AC CPU load: avg 27% (peak 30%)

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$ npm install -g metrillm@latest

$ metrillm

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Or run without installing: npx metrillm@latest