Side by side
See the difference.
Scores, capabilities and costs for the models you’re considering.
Scroll to compare models →
| 2 models | nvidiaNemotron-3-Embed-8BRemove × | intfloatIntfloat: E5-Base-v2Remove × |
|---|---|---|
| What’s different | 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… | The 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… |
| Date | Jul 16, 2026Listed | Nov 22, 2023Listed |
API prices USD · provider configuration shown below | ||
| Listed rate | See provider quotes | $0.005 in / $0.00 out/ 1M tokensOpenRouter · all routes ↗ |
| Provider endpoints | 0 endpoints → | 1 endpoint → |
Specifications | ||
| Context window | 32.8K | 512 |
| Max output | — | 460 |
| Parameters | 8B | — |
| Open weights | Not reported | Supported |