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Comparison of Intfloat: E5-Base-v2, multilingual-e5-large-instruct, Krea 3 Edit
3 modelsintfloatIntfloat: E5-Base-v2Remove ×intfloatmultilingual-e5-large-instructRemove ×kreaKrea 3 EditRemove ×
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:”…Edits and combines reference images using text instructions, with optional prompt expansion, output-size controls, and reproducible generation through a seed.
DateNov 22, 2023ListedApr 17, 2025ListedOct 14, 2026Listed
Listed rate$0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗See provider quotes$0.025/ megapixelfal · all routes ↗Output + reference images
Provider endpoints1 endpoint →0 endpoints →1 endpoint →
Context window512512—
Max output460——
Parameters———
Open weightsSupportedNot reportedNot reported

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