Benchmark result

google/gemma-4-e2b on NVIDIA GeForce RTX 3060 Laptop GPU — 104.9 tok/s

Measured with Bionic manual on October 12, 2026.

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What the model built

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The coding scenario asks for a playable game in a single HTML file. This is exactly what the model returned, unedited; the frame only adds a line that tells this page how tall it is.

How this run compares

4th fastest of 4 runs of this model on NVIDIA GeForce RTX 3060 Laptop GPU · median 105.3 tok/s.

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google/gemma-4-e2b on other hardware

Reproduce this run

toolBionic manual
modelgoogle/gemma-4-e2b
context8,192
thinkingoff
clientv0.4.92+102

Set those in Bionic, then:

llm-benchmark benchmark --model "google/gemma-4-e2b" --tool "Bionic"

The client prompts for context length and thinking mode, and for the KV cache dtype on Unsloth Studio. Sampling is left at the model default — the values above are what the tool reported using, not overrides the client sent.