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Comparison of embeddinggemma-2, Intfloat: Multilingual-E5-Large, Respan: Span-02
3 modelsgoogleembeddinggemma-2Remove ×intfloatIntfloat: Multilingual-E5-LargeRemove ×respanRespan: Span-02Remove ×
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,…The 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…Set a thinking deadline in milliseconds; returns typed decisions or direct numbers with confidence, and accepts up to four images.
DateOct 8, 2026ListedJun 4, 2024ListedOct 16, 2026Listed
Listed rateSee provider quotes$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints0 endpoints →1 endpoint →1 endpoint →
Context window8.2K512131.1K
Max output—460118K
Parameters———
Image inputNot reportedNot reportedSupported
Open weightsNot reportedSupportedNot reported

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