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Comparison of embeddinggemma-2, embeddinggemma-300m, VoyageAI by MongoDB: voyage-4
3 modelsgoogleembeddinggemma-2Remove ×googleembeddinggemma-300mRemove ×voyageaiVoyageAI by MongoDB: voyage-4Remove ×
What’s differentEmbeddingGemma 2 is a 740M parameter multimodal embedding model from Google DeepMind that maps text (incl. code), images, video and audio, alone or interleaved, into a single 768-dimensional vector space,…EmbeddingGemma is a 300M parameter multilingual open embedding model from Google DeepMind, designed for efficient deployment even on low-resource devices, producing high-quality text vector representations…voyage-4 is a general-purpose (including multilingual) embedding model optimized for retrieval/search and AI applications. voyage-4 supports embeddings in 2048, 1024, 512, and 256 dimensions, with multiple…
DateOct 8, 2026ListedSep 16, 2025ListedJul 27, 2026Listed
Listed rateSee provider quotesSee provider quotes$0.06 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints0 endpoints →0 endpoints →1 endpoint →
Context window8.2K2K32K
Max output——28.8K
Parameters—300M—

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