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Comparison of Intfloat: E5-Base-v2, Nemotron-3-Diarization, embeddinggemma-2
3 modelsintfloatIntfloat: E5-Base-v2Remove ×nvidiaNemotron-3-DiarizationRemove ×googleembeddinggemma-2Remove ×
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…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,…
DateNov 22, 2023ListedSep 25, 2026ListedOct 8, 2026Listed
Listed rate$0.005 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

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