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google/gemma-4-e4b

LM-STUDIO GGUF

gemma4 · Q4_K_M

Good

Jul 7, 2026 · AMD Ryzen 7 5800H

lfm2.5:8b

OLLAMA GGUF

lfm2moe · 8.5B · Q4_K_M

Excellent

Aug 24, 2026 · Apple M1 Pro

Global Score
68 vs 80
Hardware Fit
93 vs 95
Quality Score
57 vs 73

Hardware

google/gemma-4-e4b lfm2.5:8b
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 lfm2.5:8b
Tokens/sec26.298.5
First chunk17 ms167 ms
TTFT572 ms2.5 s
Load timeN/A3.0 s
Memory usage6.5 GB6.0 GB
Memory %41%37%

HW Fit Score Breakdown

google/gemma-4-e4b

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

lfm2.5:8b

Speed
50/50
TTFT
17/20
Memory
28/30

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

lfm2.5:8b

Reasoning
2/20
Coding
12/20
Instruction
19/20
Structured
15/15
Math
15/15
Multilingual
10/10
Reasoning: Poor Coding: Adequate Instruction Following: Strong Structured Output: Strong Math: Strong Multilingual: Strong
View google/gemma-4-e4b details | View lfm2.5:8b details

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$ npm install -g metrillm@latest
$ metrillm

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Or run without installing: npx metrillm@latest