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Gemma 4 E2B

Google · open weight · gemma-4-e2b-it

Gemma 4 E2B is Google DeepMind's smallest multimodal model with 2.3 billion effective parameters (5.1B with embeddings) and a 128K context window. Supports image, text, and audio inputs. Designed for on-device and edge deployment with Per-Layer Embeddings for efficient inference.

MMLU-ProMMMU-ProGPQA

Benchmark scores

BenchmarkScore
MMLU-Pro0.60
MMMU-Pro0.44
GPQA0.43

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AA metrics

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Arena Elo

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Gemma 4 E2B Benchmarks · all the models