Side by side

See the difference.

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

Scroll to compare models →

Comparison of Intfloat: Multilingual-E5-Large, Nemotron-3-Diarization, embeddinggemma-2
3 modelsintfloatIntfloat: Multilingual-E5-LargeRemove ×nvidiaNemotron-3-DiarizationRemove ×googleembeddinggemma-2Remove ×
What’s differentThe 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…Nemotron 3 Diarization is an open-weight streaming Sortformer model, engineered for low-latency speaker diarization across up to 8 speakers, ordered by arrival time. It powers meeting transcription, call…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,…
DateJun 4, 2024ListedSep 25, 2026ListedOct 8, 2026Listed
Listed rate$0.01 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗$0.00001/ secondDeepInfra · all routes ↗Input audio secondSee provider quotes
Provider endpoints1 endpoint →1 endpoint →0 endpoints →
Context window512—8.2K
Max output460——
Parameters———
Open weightsSupportedNot reportedNot reported

Add another model

Search all models →