qwen3.5:4b-mlx

nvfp4

THINKING MODEL

Mac mini (Apple M2)

8 GB · macOS 26.5.2

Tested on August 24, 2026 · Submitted by littleAI

Top 86% Compare

Global Score

53 /100

Marginal

Hardware Fit

82/100

Quality

41/100

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Hardware

Machine: Mac mini
CPU: Apple M2
Cores: 8 total (4 perf + 4 eff)
Frequency: 2.4 GHz
RAM: 8 GB LPDDR5
GPU: Apple M2
OS: macOS 26.5.2
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 24.7
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.1
First chunk latency Delay before the first streamed chunk arrives from runtime: 302 ms
Time to first token How fast the model starts responding — lower is better: 7.4 s
Load time Time to load the model into memory before inference: 3.2 s
Memory usage RAM consumed during inference — percentage of total system memory: 3.8 GB (47%)
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: ~727

Score breakdown

Speed

50/50

Time to first token

6/20

Memory

26/30

Quality

Reasoning

13/20

Coding

2/20

Instruction following

4/20

Structured output

4/15

Math

10/15

Multilingual

8/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.32.15
Model format: GGUF
Hardware profile: ENTRY
Result hash: d4d4a9a809e5957bc185ba29199d99501fda44838496e899b4f7425c62d7fe8f

Interpretation

Hardware fit: 82/100. Overall suitability: MARGINAL (Global 53/100). Category profile: Reasoning: Adequate, Coding: Poor, Instruction Following: Poor, Structured Output: Weak, Math: Adequate, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 12% (peak 21%)

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