qwen3.5-9b-mlx

qwen3_5 · 9B · 4bit

THINKING MODEL

Mac mini (Apple M4)

24 GB · macOS 26.3

Tested on March 11, 2026 · Submitted by cryptoepops
Top 67% Compare
Global Score
59 /100
Marginal
Hardware Fit
65/100
Quality
57/100

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Hardware

Machine
Mac mini
CPU
Apple M4
Cores
10 total (4 perf + 6 eff)
Frequency
2.4 GHz
RAM
24 GB LPDDR5
GPU
Apple M4
OS
macOS 26.3
Arch
arm64
Power Mode
balanced

Performance

Tokens/sec
14.3
Standard deviation
±0.2
First chunk latency
24 ms
Time to first token
13.4 s
Load time
13.3 s
Memory usage
2.5 GB (10%)
Total tokens
1617
Thinking tokens (est.)
~614

Score breakdown

Speed
32/50
Time to first token
3/20
Memory
30/30

Quality

Reasoning
10/20
Coding
17/20
Instruction following
5/20
Structured output
9/15
Math
11/15
Multilingual
5/10

Category levels

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

Metadata

Spec version
0.2.1
Runtime
LM Studio 0.4.6+1
Model format
MLX
Hardware profile
ENTRY
Result hash
f0e821ad6d4b50ee5fac6fe21f62611e4fa4b97cf081273c9274fd12882ff5dd

Interpretation

Hardware fit: 65/100. Overall suitability: MARGINAL (Global 59/100). Category profile: Reasoning: Weak, Coding: Strong, Instruction Following: Weak, Structured Output: Adequate, Math: Adequate, Multilingual: Adequate.

Warnings

  • Token throughput is estimated from LM Studio output because native token stats were unavailable. Compare tok/s across backends cautiously.

Bench Environment

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

Run yours now

$ npm install -g metrillm@latest
$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest