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Nemotron-3-Embed-1B-BF16 is a multilingual text embedding model from NVIDIA for semantic search, retrieval and RAG pipelines. It has about 1.14B parameters, produces 2048-dimension vectors and handles up to 32k tokens of context, with reported support for 34 languages including code retrieval. The model was derived from Ministral-3-3B-Instruct-2512 through two rounds of structured pruning and distillation and is released under the OpenMDW License 1.1 with Apache 2.0 terms. A free NVIDIA NIM endpoint and the BF16 weights on Hugging Face are available, alongside an NVFP4 variant.
A workable 1.14B-parameter dense embedding model from NVIDIA. Treat the modality benchmarks above as the leading indicator of fit — composite scoring across modalities is still maturing.
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| Acer Veriton GN100 AI MiniAcer | SS | 1.5 GB |
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| AMD Instinct MI325XAMD | SS | 1.5 GB |
| AMD Instinct MI355XAMD | SS | 1.5 GB |
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Nemotron-3-Embed-1B-BF16 is a transformer text embedding encoder built by NVIDIA from the Ministral-3-3B-Instruct-2512 parent through two iterative rounds of structured pruning and distillation. It uses bidirectional attention masking and average pooling over token representations to produce a single 2048-dimension dense vector per input. NVIDIA reports it reaches top retrieval quality among models of comparable size on multilingual benchmarks, and ships a Blackwell-optimized NVFP4 sibling that retains about 99.5% of the BF16 version's reported RTEB score.
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