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google/gemma-4-e4b

LM-STUDIO GGUF

gemma4 · Q4_K_M

Good

Jul 7, 2026 · AMD Ryzen 7 5800H

smollm2:135m

OLLAMA GGUF

llama · 134.52M · F16

Marginal

Mar 2, 2026 · Apple M4

Global Score
62 vs 41
Hardware Fit
77 vs 100
Quality Score
55 vs 15

Hardware

google/gemma-4-e4b smollm2:135m
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 smollm2:135m
Tokens/sec27.6241.0
First chunk23 msN/A
TTFT480 ms39 ms
Load timeN/A0.4 s
Memory usage13.2 GB0.6 GB
Memory %83%2%

HW Fit Score Breakdown

google/gemma-4-e4b

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

smollm2:135m

Speed
40/50
TTFT
30/20
Memory
30/30

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

smollm2:135m

Reasoning
4/20
Coding
1/20
Instruction
6/20
Structured
2/15
Math
1/15
Multilingual
1/10
Reasoning: Poor Coding: Poor Instruction Following: Weak Structured Output: Poor Math: Poor Multilingual: Poor
View google/gemma-4-e4b details | View smollm2:135m details

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$ metrillm

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Or run without installing: npx metrillm@latest