Side by side
See the difference.
Scores, capabilities and costs for the models you’re considering.
Scroll to compare models →
| 3 models | Unknowntext-embedding-3-smallRemove × | nvidiaNemotron-3-Embed-8BRemove × | googleembeddinggemma-2Remove × |
|---|---|---|---|
| What’s different | 8.2K context | Nemotron-3-Embed-8B is a multilingual text embedding model from NVIDIA, based on Ministral-3-8B, that maps text into 4096-dimensional dense vectors for retrieval and semantic similarity. Spanning 34… | 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,… |
| Date | Oct 16, 2026Discovered | Jul 16, 2026Listed | Oct 8, 2026Listed |
API prices USD · provider configuration shown below | |||
| Listed rate | $0.02 in / $0.00 out/ 1M tokensExperiential · all routes ↗Standard list rate | See provider quotes | See provider quotes |
| Provider endpoints | 1 endpoint → | 0 endpoints → | 0 endpoints → |
Specifications | |||
| Context window | 8.2K | 32.8K | 8.2K |
| Max output | — | — | — |
| Parameters | — | 8B | — |