hf.co/empero-ai/Qwen3.8-2B-Distill-GGUF:BF16
OLLAMA GGUFqwen35 · 1.94B · BF16
Aug 22, 2026 · Apple M1 Pro
google/gemma-4-e4b
LM-STUDIO GGUFgemma4 · Q4_K_M
Jul 7, 2026 · AMD Ryzen 7 5800H
Global Score
66 vs 62
Hardware Fit
100 vs 77
Quality Score
52 vs 55
Hardware
hf.co/empero-ai/Qw… google/gemma-4-e4b
MachineMacBook ProLENOVO 82JQ
CPUApple M1 ProAMD Ryzen 7 5800H
Cores1016
RAM16 GB16 GB
GPUApple M1 ProNVIDIA GeForce RTX 3060 Laptop GPU
OSmacOS 26.6.2Microsoft Windows 11 家庭版 中文版 10.0.26100
Archarm64x64
Power Modebalancedbalanced
Performance
hf.co/empero-ai/Qw… google/gemma-4-e4b
Tokens/sec40.227.6
First chunk325 ms23 ms
TTFT325 ms480 ms
Load time3.1 sN/A
Memory usage4.7 GB13.2 GB
Memory %30%83%
HW Fit Score Breakdown
hf.co/empero-ai/Qwen3.8…
Speed
50/50
TTFT
20/20
Memory
30/30
google/gemma-4-e4b
Speed
48/50
TTFT
20/20
Memory
9/30
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
google/gemma-4-e4b
Reasoning
18/20
Coding
17/20
Instruction
5/20
Structured
3/15
Math
11/15
Multilingual
1/10
Reasoning: Strong Coding: Strong Instruction Following: Weak Structured Output: Poor Math: Strong Multilingual: Poor
Run yours and compare
$
npm install -g metrillm@latest$
metrillmRequires Node 20+ and Ollama or LM Studio running
Or run without installing: npx metrillm@latest