NVIDIA Nemotron 3 Embed Tops Retrieval Benchmarks
NVIDIA released Nemotron 3 Embed, a family of open embedding models with an 8B flagship that ranks #1 on the RTEB leaderboard, plus optimized 1B variants for production-scale retrieval.
Why it matters
High-quality retrieval is crucial for reducing agentic token costs and improving the relevance of context in multi-step workflows.
TL;DR
- 01Flagship 8B model ranks #1 on the RTEB leaderboard.
- 021B models offer high-efficiency options for production RAG.
- 03Models support multilingual and code retrieval.
- 04NVFP4 quantization helps optimize performance on Blackwell hardware.
State-of-the-Art Retrieval
NVIDIA Nemotron 3 Embed models are designed to solve retrieval inefficiencies. The flagship Nemotron-3-Embed-8B-BF16 reached the top spot on the RTEB leaderboard. The Nemotron-3-Embed-1B-BF16 variant offers high-efficiency retrieval for production environments, showing significant error rate reductions compared to its predecessor.
Blackwell-Optimized Efficiency
For high-throughput requirements, the Nemotron-3-Embed-1B-NVFP4 variant utilizes 4-bit quantization and Quantization-Aware Distillation (QAD) to maintain retrieval accuracy while maximizing throughput on Blackwell architecture.