Side by side
See the difference.
Scores, capabilities and costs for the models you’re considering.
Scroll to compare models →
| 3 models | Unknownseed-2.0-codeRemove × | googleembeddinggemma-2Remove × | nvidiaNemotron-3-DiarizationRemove × |
|---|---|---|---|
| What’s different | 262.1K context · 131.1K max output · Tool calling · Structured output | 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,… | 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… |
| Date | Oct 16, 2026Discovered | Oct 8, 2026Listed | Sep 25, 2026Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | $0.50 in / $3.00 out/ 1M tokensExperiential · all routes ↗Standard · fewer than 128,001 input tokens | See provider quotes | $0.00001/ secondDeepInfra · all routes ↗Input audio second |
| Provider endpoints | 1 endpoint → | 0 endpoints → | 1 endpoint → |
Specifications | |||
| Context window | 262.1K | 8.2K | — |
| Max output | 131.1K | — | — |
| Parameters | — | — | — |
| Tool calling | Supported | Not reported | Not reported |
| Structured output | Supported | Not reported | Not reported |
| Reasoning | Supported | Not reported | Not reported |