Side by side

See the difference.

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

Scroll to compare models →

Comparison of Intfloat: E5-Large-v2, Krea: K3 Edit, embeddinggemma-2
3 modelsintfloatIntfloat: E5-Large-v2Remove ×kreaKrea: K3 EditRemove ×googleembeddinggemma-2Remove ×
What’s differentThe 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.EmbeddingGemma 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,…
DateNov 22, 2023ListedOct 15, 2026ListedOct 8, 2026Listed
Listed rate$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗See provider quotesSee provider quotes
Provider endpoints1 endpoint →0 endpoints →0 endpoints →
Context window51265.5K8.2K
Max output46059K—
Parameters———
Image inputNot reportedSupportedNot reported
Open weightsSupportedNot reportedNot reported

Add another model

Search all models →