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Comparison of Intfloat: E5-Base-v2, multilingual-e5-large-instruct, LiquidAI: d1-ultra
3 modelsintfloatIntfloat: E5-Base-v2Remove ×intfloatmultilingual-e5-large-instructRemove ×liquidLiquidAI: d1-ultraRemove ×
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…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:”…d1-ultra is Liquid AI's largest decision model, served as a System One endpoint. Send a state of text and images along with typed questions, and it returns a choice, a...
DateNov 22, 2023ListedApr 17, 2025ListedOct 15, 2026Listed
Listed rate$0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗See provider quotes$0.042 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗
Provider endpoints1 endpoint →0 endpoints →1 endpoint →
Context window51251232.8K
Max output460—29.5K
Parameters———
Image inputNot reportedNot reportedSupported
Prompt cachingNot reportedNot reportedSupported
Open weightsSupportedNot reportedNot reported

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