Side by side

See the difference.

Scores, capabilities and costs for the models you’re considering.

Scroll to compare models →

Comparison of multilingual-e5-large-instruct, Intfloat: E5-Large-v2, Krea: K3 Edit
3 modelsintfloatmultilingual-e5-large-instructRemove ×intfloatIntfloat: E5-Large-v2Remove ×kreaKrea: K3 EditRemove ×
What’s differentThe 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:”…The e5-large-v2 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-accuracy semantic embeddings optimized for retrieval, semantic…Edits one to eight reference images from a text prompt, returning one image.
DateApr 17, 2025ListedNov 22, 2023ListedOct 15, 2026Listed
Listed rateSee provider quotes$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗See provider quotes
Provider endpoints0 endpoints →1 endpoint →0 endpoints →
Context window51251265.5K
Max output—46059K
Parameters———
Image inputNot reportedNot reportedSupported
Open weightsNot reportedSupportedNot reported

Add another model

Search all models →