Back to leaderboard

google/gemma-4-e4b

LM-STUDIO GGUF

gemma4 · Q4_K_M

Good

Jul 7, 2026 · AMD Ryzen 7 5800H

qwen3:8b

OLLAMA GGUF

qwen3 · 8.2B · Q4_K_M

Excellent

Mar 5, 2026 · Intel Core™ Ultra 9 285K

Global Score
62 vs 84
Hardware Fit
77 vs 97
Quality Score
55 vs 79

Hardware

google/gemma-4-e4b qwen3:8b
MachineLENOVO 82JQASUS
CPUAMD Ryzen 7 5800HIntel Core™ Ultra 9 285K
Cores1624
RAM16 GB47 GB
GPUNVIDIA GeForce RTX 3060 Laptop GPUNVIDIA GeForce RTX 5090, Intel(R) Graphics
OSMicrosoft Windows 11 家庭版 中文版 10.0.26100Microsoft Windows 11 Pro 10.0.26200
Archx64x64
Power Modebalancedbalanced

Performance

google/gemma-4-e4b qwen3:8b
Tokens/sec27.6208.0
First chunk23 ms82 ms
TTFT480 ms1.3 s
Load timeN/A1.5 s
Memory usage13.2 GB9.6 GB
Memory %83%20%

HW Fit Score Breakdown

google/gemma-4-e4b

Speed
48/50
TTFT
20/20
Memory
9/30

qwen3:8b

Speed
50/50
TTFT
18/20
Memory
29/30

Quality

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

qwen3:8b

Reasoning
18/20
Coding
10/20
Instruction
14/20
Structured
15/15
Math
12/15
Multilingual
10/10
Reasoning: Strong Coding: Weak Instruction Following: Adequate 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