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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

Mar 6, 2026 · Apple M4

Global Score
68 vs 76
Hardware Fit
93 vs 89
Quality Score
57 vs 71

Hardware

google/gemma-4-e4b ministral-3:8b
MachineLENOVO 82JQMacBook Air
CPUAMD Ryzen 7 5800HApple M4
Cores1610
RAM16 GB32 GB
GPUNVIDIA GeForce RTX 3060 Laptop GPUApple M4
OSMicrosoft Windows 11 家庭版 中文版 10.0.26100macOS 26.3
Archx64arm64
Power Modebalancedbalanced

Performance

google/gemma-4-e4b ministral-3:8b
Tokens/sec26.219.5
First chunk17 ms328 ms
TTFT572 ms328 ms
Load timeN/A1.5 s
Memory usage6.5 GB10.6 GB
Memory %41%33%

HW Fit Score Breakdown

google/gemma-4-e4b

Speed
46/50
TTFT
20/20
Memory
27/30

ministral-3:8b

Speed
39/50
TTFT
20/20
Memory
30/30

Quality

google/gemma-4-e4b

Reasoning
17/20
Coding
19/20
Instruction
4/20
Structured
4/15
Math
12/15
Multilingual
1/10
Reasoning: Strong Coding: Strong Instruction Following: Poor Structured Output: Weak Math: Strong Multilingual: Poor

ministral-3:8b

Reasoning
12/20
Coding
18/20
Instruction
12/20
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