Side by side

See the difference.

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

Scroll to compare models →

Comparison of embeddinggemma-2, Intfloat: Multilingual-E5-Large, Ideogram V4.5 Edit
3 modelsgoogleembeddinggemma-2Remove ×intfloatIntfloat: Multilingual-E5-LargeRemove ×ideogramIdeogram V4.5 EditRemove ×
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-large embedding model encodes sentences, paragraphs, and documents across over 90 languages into a 1024-dimensional dense vector space, delivering robust semantic embeddings optimized…Mask-guided edits with a high-precision mode that restores unchanged pixels; combines a source image with extra references.
DateOct 8, 2026ListedJun 4, 2024ListedSep 30, 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 window8.2K512—
Max output—460—
Parameters———
Open weightsNot reportedSupportedNot reported

Add another model

Search all models →