EmbeddingGemma 2 Delivers Best-in-Class Performance at 740M Parameters
Original titleBest-in-class for its size at 740M parameters, EmbeddingGemma 2 outperforms some models over twice its size while using from as little as...
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Google's EmbeddingGemma 2 is a 740M-parameter embedding model that outperforms some models more than twice its size while using about 191MB to 567MB of active RAM. It offers an 8K context window, 4x larger than the first generation, and can process up to 5.5 minutes of audio, 29 images, or 58 video frames in one pass.
Source: Google · x.comPublished · added here