What changed
Implemented low-precision NVFP4 pretraining with latent-expert Mamba/attention hybrids and native multi-token prediction, then consolidated specialist agentic teachers in the Ultra post-training system.
Scientific scope
Implemented low-precision NVFP4 pretraining with latent-expert Mamba/attention hybrids and native multi-token prediction, then consolidated specialist agentic teachers in the Ultra post-training system. Super and Ultra are bundled as one realized system-family delta beyond Nano, not separate achievements by size. LatentMoE, Mamba and speculative decoding have their own prior sources; architecture and throughput are configuration-specific. Earlier family plans are not realized 2025 capabilities.
Evidence
The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Super and Ultra are bundled as one realized system-family delta beyond Nano, not separate achievements by size. LatentMoE, Mamba and speculative decoding have their own prior sources; architecture and throughput are configuration-specific. Earlier family plans are not realized 2025 capabilities.
Contributors
- Source-listed authors and technical contributors · SCIENCE: Source-listed authors or explicitly credited technical contributors for the cited versions. Family entries retain source-specific attribution; a combined list is not one original-paper byline or equal individual work. Names alone do not establish resolved identities.
- Nemotron 3 Super: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
- Nemotron 3 Ultra: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic Reasoning
- NVIDIA: Nemotron 3 NVFP4 hybrid expert-training system — official research account
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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B