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Comparison of Intfloat: Multilingual-E5-Large, Google: Gemini Embedding 2
2 modelsintfloatIntfloat: Multilingual-E5-LargeRemove ×googleGoogle: Gemini Embedding 2Remove ×
What’s differentThe multilingual-e5-large embedding model encodes sentences, paragraphs, and documents across over 90 languages into a 1024-dimensional dense vector space, delivering robust semantic embeddings optimized…Gemini Embedding 2 is Google's first multimodal embedding model. We currently support mapping text and images into a unified vector space for semantic search and retrieval-augmented generation (RAG). It…
DateJun 4, 2024ListedMay 20, 2026Listed
Listed rate$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.20 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints1 endpoint →1 endpoint →
Context window5128.2K
Max output4607.4K
Parameters——
Image inputNot reportedSupported
Audio inputNot reportedSupported
Video inputNot reportedSupported
Open weightsSupportedNot reported

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