Nemotron 3 Ultra Model to write, debug and explain code
NVIDIA Chat and reasoning models Upgrade to use nvidia/nemotron-3-ultra-550b-a55b
A description page for NVIDIA Nemotron 3 Ultra, the 550B open frontier model designed for long-running agents, multi-step reasoning and code generation. This page helps developers and engineering teams decide when to run Nemotron 3 Ultra on production agents or heavy-code workloads.
What it can do
- Searches the live web and cites sources
- Thinks step by step on hard questions
What people use it for
Automated code generation and review
Generate, explain and fix multi-file code with automated unit test checks and iterative prompts. Nemotron 3 Ultra handles complex code context across files and retains execution traces for stepwise debugging, making it useful for engineering assistants and CI integrations.
Long-running research and document analysis
Work with large technical documents, notebooks or datasets using a 1M token context window to keep research context in a single session. Use it for report synthesis, code-aware literature review and chained reasoning across long inputs.
Agent orchestration and planning
Use Nemotron 3 Ultra as the core reasoner in multi-step agents that plan, route and call tools. Its Mixture-of-Experts design gives strong agentic reasoning while maintaining efficient inference through NVFP4 optimizations.
Why it is worth it
- Open weights and deployment options for on-prem and cloud inference.
- Engineered for high-throughput inference with NVFP4 quantization support.
- Support for long contexts up to one million tokens for persistent sessions.
- Designed to keep reasoning traces and planned steps across long agent runs.
Questions people ask
What is Nemotron 3 Ultra good at compared with smaller models?
Nemotron 3 Ultra is built for complex, multi-step reasoning, agent orchestration and large-context code work rather than lightweight chat. It uses a Mixture-of-Experts architecture that activates fewer parameters per step to scale reasoning with lower inference cost than naive dense models.
How large is the model and what context length does it support?
The model is a 550 billion parameter Nemotron 3 Ultra with roughly 55 billion active parameters in the MoE routing configuration, and it supports context lengths up to one million tokens for long-running sessions.
How is Katteb billing handled for this model?
On Katteb Chat this model costs 8 credits per message billed on actual token usage. You can switch models mid-conversation and pay only for messages you send with Nemotron 3 Ultra.
