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google/gemma-4-e4b

LM-STUDIO GGUF

gemma4 · Q4_K_M

Good

Jul 7, 2026 · AMD Ryzen 7 5800H

mistral-nemo:12b

OLLAMA GGUF

llama · 12.2B · Q4_0

Good

Mar 1, 2026 · Apple M4

Global Score
62 vs 71
Hardware Fit
77 vs 86
Quality Score
55 vs 65

Hardware

google/gemma-4-e4b mistral-nemo:12b
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 mistral-nemo:12b
Tokens/sec27.614.6
First chunk23 msN/A
TTFT480 ms371 ms
Load timeN/A1.0 s
Memory usage13.2 GB13.3 GB
Memory %83%42%

HW Fit Score Breakdown

google/gemma-4-e4b

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

mistral-nemo:12b

Speed
26/50
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

mistral-nemo:12b

Reasoning
12/20
Coding
13/20
Instruction
11/20
Structured
15/15
Math
4/15
Multilingual
10/10
Reasoning: Adequate Coding: Adequate Instruction Following: Adequate Structured Output: Strong Math: Poor Multilingual: Strong
View google/gemma-4-e4b details | View mistral-nemo:12b details

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$ npm install -g metrillm@latest
$ metrillm

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Or run without installing: npx metrillm@latest