Embedding models decide which passages an agent ever sees. NVIDIA released Nemotron 3 Embed model to work on that layer. It targets production-scale RAG, agentic retrieval, code retrieval, and agent memory.
What is Nemotron 3 Embed?
The model collection includes three open checkpoints. Nemotron-3-Embed-8B-BF16 is the accuracy-first option. Nemotron-3-Embed-1B-BF16 carries the same design into a smaller footprint. Nemotron-3-Embed-1B-NVFP4 is the Blackwell-optimized 4-bit path.
All three are transformer encoders trained with bidirectional attention masking. The final embedding comes from average pooling over token-level representations. Maximum sequence length is 32,768 tokens on every checkpoint.
Each model was evaluated across 34 languages. All three carry the OpenMDW License Agreement, version 1.1 (OpenMDW-1.1). Notably, the bases are Mistral models. The 8B is built with Ministral-3-8B-Instruct-2512. Both 1B variants use Ministral-3-3B-Instruct-2512.
