Back to leaderboard

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

OLLAMA GGUF

qwen35 · 1.94B · BF16

Good

Aug 26, 2026 · Apple M1 Pro

gemma-4-26b-a4b-it@iq3_xxs

LM-STUDIO GGUF

gemma4 · 26B · IQ3_XXS

Excellent

Jun 29, 2026 · Intel Gen Intel® Core™ i9-11900H

Global Score
66 vs 83
Hardware Fit
100 vs 58
Quality Score
52 vs 94

Hardware

hf.co/empero-ai/Qw… gemma-4-26b-a4b-it…
MachineMacBook ProDocker Container
CPUApple M1 ProIntel Gen Intel® Core™ i9-11900H
Cores1016
RAM16 GB15 GB
GPUApple M1 ProTigerLake-H GT1 [UHD Graphics]
OSmacOS 26.6.2Ubuntu 26.04 LTS
Archarm64x64
Power Modebalancedperformance

Performance

hf.co/empero-ai/Qw… gemma-4-26b-a4b-it…
Tokens/sec40.210.3
First chunk101 ms8 ms
TTFT101 ms3.5 s
Load time2.6 s10.9 s
Memory usage4.7 GB6.4 GB
Memory %30%41%

HW Fit Score Breakdown

hf.co/empero-ai/Qwen3.8…

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

gemma-4-26b-a4b-it@iq3_…

Speed
19/50
TTFT
12/20
Memory
27/30

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

gemma-4-26b-a4b-it@iq3_…

Reasoning
18/20
Coding
19/20
Instruction
19/20
Structured
15/15
Math
14/15
Multilingual
9/10
Reasoning: Strong Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Strong Multilingual: Strong

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