EmbeddingGemma 2 is an open multimodal embedding model that natively represents text, images, audio, video, and their combinations in a unified space. It introduces simplified per‑layer embeddings and a multi‑stage curriculum that improves quality across unimodal, cross‑modal, and mixed‑modal tasks. The model sets a new Pareto frontier in comprehensive benchmarks, outperforming specialist and larger models, while offering flexibility for resource‑constrained settings through selective encoder loading, adjustable token budgets, truncatable dimensions, and quantized weights.
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