Google’s AI EmbeddingGemma is Breaking Records

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Google’s AI EmbeddingGemma is Breaking Records

Google just surprised the AI world with a model that’s tiny, offline, and still breaking records.

EmbeddingGemma has only 308 million parameters but beats models twice its size on the toughest benchmarks. It runs in under 200MB of RAM, works fully offline on phones and laptops, and understands over 100 languages, all while delivering blazing-fast embeddings in under 15 milliseconds.

With Matryoshka learning, it scales down vectors without losing power, making it perfect for private search, RAG pipelines, and fine-tuning on everyday GPUs.

This might be Google’s most practical AI release yet.

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Google’s AI EmbeddingGemma is Breaking Records

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