NVIDIA Nemotron 3 Ultra: Open Frontier LLM for Agentic Reasoning

Model Overview

NVIDIA Nemotron 3 Ultra is a flagship open-weight frontier large language model family developed by NVIDIA. It is engineered specifically for agentic AI workloads, long-context understanding, multi-step complex reasoning, automated coding, and tool calling.

The family includes the Nemotron 3 Ultra 550B (a hybrid Transformer-Mamba LatentMoE model with 55B active parameters per token and up to 1M token context) and Llama-3.1-Nemotron-Ultra-253B-v1 (a dense 253B model optimized for single-node 8xH100/B200 enterprise deployment).

---

Key Features

• Hybrid LatentMoE & Mamba-2 Architecture: Combines Mamba-2 state space model layers with Latent Mixture-of-Experts (550B total / 55B active parameters) to maximize throughput and long-sequence processing.
• Dual-Mode System: Features configurable low-latency chat (reasoning off) and extended Chain-of-Thought (reasoning on) modes controlled via prompt parameters.
• Ultra-Long Context Window: Supports up to 1,000,000 (1M) tokens context window (550B MoE) and 128,000 (128K) tokens (253B Dense).
• Native NVFP4 Quantization: Native NVFP4 4-bit floating-point quantization enables single-node enterprise inference with up to 5x throughput speedups.
• Agentic Post-Training: Multi-environment RL post-training tailored for function calling (BFCL), complex multi-turn execution, automated coding (SWE-bench), and RAG.

---

Verified Project Links

• Developer Blog: https://developer.nvidia.com/blog/nvidia-releases-nemotron-ultra
• Technical Report (arXiv): https://arxiv.org/abs/2512.20856
• GitHub Repository: https://github.com/NVIDIA/NeMo
• Hugging Face Model: https://huggingface.co/nvidia/Llama-3_1-Nemotron-Ultra-253B-v1

---

Performance & Benchmarks

• MMLU-Pro (550B MoE): 86.8%
• SWE-bench Verified (550B MoE): 70.7%
• MATH-500 (253B Reasoning On): 97.0%
• BFCL v2 Tool Calling (253B): 74.1%