qwen3:14b

qwen3 · 14.8B · Q4_K_M

Mac mini (Apple M4)

24 GB · macOS 26.3

Tested on March 19, 2026 · Submitted by cryptoepops

Top 13% Compare

Global Score

82 /100

Excellent

Hardware Fit

71/100

Quality

86/100

Get this model

🦙

Ollama

ollama pull qwen3:14b

View on Ollama Library

ollama.com/library/qwen3

Get it in LM Studio

Search and download models directly from the app

🤗

Find on HuggingFace

GGUF versions & quantizations

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 Tokens generated per second — higher is better: 10.3
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: 513 ms
Time to first token How fast the model starts responding — lower is better: 513 ms
Load time Time to load the model into memory before inference: 7.2 s
Memory usage RAM consumed during inference — percentage of total system memory: 9.4 GB (39%)
Total tokens Total number of tokens generated across all benchmark prompts: 962

Score breakdown

Speed

23/50

Time to first token

20/20

Memory

28/30

Quality

Reasoning

17/20

Coding

18/20

Instruction following

14/20

Structured output

15/15

Math

12/15

Multilingual

10/10

Category levels

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

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.17.7
Model format: GGUF
Hardware profile: ENTRY
Result hash: e42021b0774a2b3281d6767cb8e5cba66408869840e0527adf5f360d89fc3932

Interpretation

Hardware fit: 71/100. Overall suitability: EXCELLENT (Global 82/100). Category profile: Reasoning: Strong, Coding: Strong, Instruction Following: Adequate, Structured Output: Strong, Math: Strong, Multilingual: Strong.

Bench Environment

Power: AC CPU load: avg 13% (peak 16%)

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