Back to leaderboard

google/gemma-4-e4b

LM-STUDIO GGUF

gemma4 · Q4_K_M

Good

Jul 7, 2026 · AMD Ryzen 7 5800H

ministral-3:8b

OLLAMA GGUF

mistral3 · 8.9B · Q4_K_M

Good

Aug 25, 2026 · Apple M1 Pro

Global Score
62 vs 72
Hardware Fit
77 vs 71
Quality Score
55 vs 72

Hardware

google/gemma-4-e4b ministral-3:8b
MachineLENOVO 82JQMacBook Pro
CPUAMD Ryzen 7 5800HApple M1 Pro
Cores1610
RAM16 GB16 GB
GPUNVIDIA GeForce RTX 3060 Laptop GPUApple M1 Pro
OSMicrosoft Windows 11 家庭版 中文版 10.0.26100macOS 26.6.2
Archx64arm64
Power Modebalancedbalanced

Performance

google/gemma-4-e4b ministral-3:8b
Tokens/sec27.619.8
First chunk23 ms269 ms
TTFT480 ms269 ms
Load timeN/A10.7 s
Memory usage13.2 GB13.7 GB
Memory %83%86%

HW Fit Score Breakdown

google/gemma-4-e4b

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

ministral-3:8b

Speed
44/50
TTFT
20/20
Memory
7/30

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

ministral-3:8b

Reasoning
12/20
Coding
18/20
Instruction
13/20
Structured
13/15
Math
6/15
Multilingual
10/10
Reasoning: Adequate Coding: Strong Instruction Following: Adequate Structured Output: Strong Math: Weak Multilingual: Strong
View google/gemma-4-e4b details | View ministral-3:8b 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