gemma4:e2b

gemma4 · 5.1B · Q4_K_M

AZW GTR Pro (AMD RYZEN AI MAX+ 395)

125 GB · Ubuntu 24.04.4 LTS

Tested on April 3, 2026

Top 14% Compare

Global Score

83 /100

Excellent

Hardware Fit

100/100

Quality

76/100

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Ollama

ollama pull gemma4:e2b

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ollama.com/library/gemma4

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GGUF versions & quantizations

Hardware

Machine: AZW GTR Pro
CPU: AMD RYZEN AI MAX+ 395
Cores: 32 threads (16 cores)
Frequency: 3 GHz
RAM: 125 GB
GPU: Radeon 8060S
OS: Ubuntu 24.04.4 LTS
Arch: x64
Power Mode: performance

Performance

Tokens/sec Tokens generated per second — higher is better: 88.1
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±0.5
First chunk latency Delay before the first streamed chunk arrives from runtime: 193 ms
Time to first token How fast the model starts responding — lower is better: 193 ms
Load time Time to load the model into memory before inference: 2.7 s
Memory usage RAM consumed during inference — percentage of total system memory: 11.2 GB (9%)
Total tokens Total number of tokens generated across all benchmark prompts: 1039

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

12/20

Coding

16/20

Instruction following

15/20

Structured output

15/15

Math

8/15

Multilingual

10/10

Category levels

Reasoning: Adequate Coding: Strong Instruction Following: Strong Structured Output: Strong Math: Adequate Multilingual: Strong

Metadata

Spec version: 0.2.1
Runtime: Ollama 0.20.0
Model format: GGUF
Hardware profile: HIGH-END
Result hash: a786467661bc0714aa0540f6045d3f7a3dae012b8ec72c2e1051dc3744c590be

Interpretation

Hardware fit: 100/100. Overall suitability: EXCELLENT (Global 83/100). Category profile: Reasoning: Adequate, Coding: Strong, Instruction Following: Strong, Structured Output: Strong, Math: Adequate, Multilingual: Strong.

Bench Environment

Thermal: nominal CPU load: avg 5% (peak 7%)

Run yours now

$ npm install -g metrillm@latest

$ metrillm

Requires Node 20+ and Ollama or LM Studio running

Or run without installing: npx metrillm@latest