Back to leaderboard

hf.co/empero-ai/Qwen3.8-2B-Distill-GGUF:BF16

OLLAMA GGUF

qwen35 · 1.94B · BF16

Good

Aug 23, 2026 · Apple M1 Pro

ministral-3-14b-instruct-2512

LM-STUDIO GGUF

mistral3 · 14B · Q5_K_M

Excellent

Jul 4, 2026 · AMD Ryzen 7 7800X3D 8-Core Processor

Global Score
66 vs 83
Hardware Fit
100 vs 90
Quality Score
52 vs 80

Hardware

hf.co/empero-ai/Qw… ministral-3-14b-in…
MachineMacBook ProASUS
CPUApple M1 ProAMD Ryzen 7 7800X3D 8-Core Processor
Cores1016
RAM16 GB31 GB
GPUApple M1 ProNVIDIA GeForce RTX 4090, Raphael
OSmacOS 26.6.2cachyos rolling
Archarm64x64
Power Modebalancedlow-power

Performance

hf.co/empero-ai/Qw… ministral-3-14b-in…
Tokens/sec40.483.7
First chunk93 ms16 ms
TTFT93 ms117 ms
Load time2.7 sN/A
Memory usage4.7 GB18.2 GB
Memory %30%60%

HW Fit Score Breakdown

hf.co/empero-ai/Qwen3.8…

Speed
50/50
TTFT
20/20
Memory
30/30

ministral-3-14b-instruc…

Speed
50/50
TTFT
20/20
Memory
20/30

Quality

hf.co/empero-ai/Qwen3.8…

Reasoning
15/20
Coding
9/20
Instruction
8/20
Structured
1/15
Math
15/15
Multilingual
4/10
Reasoning: Adequate Coding: Weak Instruction Following: Weak Structured Output: Poor Math: Strong Multilingual: Weak

ministral-3-14b-instruc…

Reasoning
17/20
Coding
17/20
Instruction
15/20
Structured
14/15
Math
7/15
Multilingual
10/10
Reasoning: Strong Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Weak Multilingual: Strong
View hf.co/empero-ai/Qw… details | View ministral-3-14b-in… details

Run yours and compare

$ npm install -g metrillm@latest
$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest