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Comparison of embeddinggemma-2, multilingual-e5-large-instruct, codestral-embed
3 modelsgoogleembeddinggemma-2Remove ×intfloatmultilingual-e5-large-instructRemove ×Unknowncodestral-embedRemove ×
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 models, initialized from XLM-RoBERTa, support up to 512 tokens per input — any longer text will be silently truncated. To ensure optimal performance, always prefix inputs with “query:”…8.2K context
DateOct 8, 2026ListedApr 17, 2025ListedOct 16, 2026Discovered
Listed rateSee provider quotesSee provider quotes$0.15 in / $0.00 out/ 1M tokensExperiential · all routes ↗Standard list rate
Provider endpoints0 endpoints →0 endpoints →1 endpoint →
Context window8.2K5128.2K
Max output———
Parameters———

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