Gemma 4 E2B

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

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.