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Comparison of Intfloat: E5-Base-v2, Google: Gemini Embedding 2
2 modelsintfloatIntfloat: E5-Base-v2Remove ×googleGoogle: Gemini Embedding 2Remove ×
What’s differentThe e5-base-v2 embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, producing efficient and high-quality semantic embeddings optimized for tasks such as…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…
DateNov 22, 2023ListedMay 20, 2026Listed
Listed rate$0.005 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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