Gemma 3n E4B Instructed LiteRT Preview

Gemma 3n is a generative AI model optimized for use in everyday devices, such as phones, laptops, and tablets. It features innovations like Per-Layer Embedding (PLE) parameter caching and a MatFormer model architecture for reduced compute and memory. These models handle audio, text, and visual data, though this E4B preview currently supports text and vision input. Gemma is a family of lightweight, state-of-the-art open models from Google, built from the same research and technology used to create the Gemini models, and is licensed for responsible commercial use.

Benchmark results

Benchmark Score Tags Source
AIME 2025 11.6% self-reported llm-stats link →
ARC-C 61.6% self-reported llm-stats link →
ARC-E 81.6% self-reported llm-stats link →
BIG-Bench Hard 52.9% self-reported llm-stats link →
BoolQ 81.6% self-reported llm-stats link →
Codegolf v2.2 16.8% self-reported llm-stats link →
DROP 60.8% self-reported llm-stats link →
ECLeKTic 1.9% self-reported llm-stats link →
Global-MMLU 60.3% self-reported llm-stats link →
Global-MMLU-Lite 64.5% self-reported llm-stats link →
GPQA 23.7% self-reported llm-stats link →
HellaSwag 78.6% self-reported llm-stats link →
HiddenMath 37.7% self-reported llm-stats link →
HumanEval 75.0% self-reported llm-stats link →
Include 57.2% self-reported llm-stats link →
LiveCodeBench 13.2% self-reported llm-stats link →
LiveCodeBench v5 25.7% self-reported llm-stats link →
MBPP 63.6% self-reported llm-stats link →
MGSM 60.7% self-reported llm-stats link →
MMLU 64.9% self-reported llm-stats link →
MMLU-Pro 50.6% self-reported llm-stats link →
MMLU-ProX 19.9% self-reported llm-stats link →
Natural Questions 20.9% self-reported llm-stats link →
PIQA 81.0% self-reported llm-stats link →
Social IQa 50.0% self-reported llm-stats link →
TriviaQA 70.2% self-reported llm-stats link →
Winogrande 71.7% self-reported llm-stats link →
WMT24++ 50.1% self-reported llm-stats link →