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google/gemma-4-e4b

LM-STUDIO GGUF

gemma4 · Q4_K_M

Good

Jul 7, 2026 · AMD Ryzen 7 5800H

wizardlm2:7b

OLLAMA GGUF

llama · 7B · Q4_0

Marginal

Mar 2, 2026 · Apple M4

Global Score
68 vs 59
Hardware Fit
93 vs 97
Quality Score
57 vs 43

Hardware

google/gemma-4-e4b wizardlm2:7b
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 wizardlm2:7b
Tokens/sec26.223.2
First chunk17 msN/A
TTFT572 ms264 ms
Load timeN/A0.6 s
Memory usage6.5 GB9.9 GB
Memory %41%31%

HW Fit Score Breakdown

google/gemma-4-e4b

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

wizardlm2:7b

Speed
37/50
TTFT
30/20
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

wizardlm2:7b

Reasoning
6/20
Coding
11/20
Instruction
10/20
Structured
4/15
Math
4/15
Multilingual
8/10
Reasoning: Weak Coding: Adequate Instruction Following: Adequate Structured Output: Weak Math: Weak Multilingual: Strong
View google/gemma-4-e4b details | View wizardlm2:7b 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