Largest Nemotron 3 model for maximum open-weight reasoning and agent accuracy
Open Nemotron omni model combining reasoning with text, vision, and audio
Nemotron middle tier for collaborative agents and high-volume reasoning workloads
Small Nemotron 3 MoE for efficient coding, math, and long-context agents
Nemotron multimodal model for visual reasoning and agentic AI workflows
Llama-3.3-Nemotron-Super-49B-v1 is a large language model (LLM) optimized for advanced reasoning, conversational interactions, retrieval-augmented generation (RAG), and tool-calling tasks. Derived from Meta's Llama-3.3-70B-Instruct, it employs a Neural Architecture Search (NAS) approach, significantly enhancing efficiency and reducing memory requirements. This allows the model to support a context length of up to 128K tokens and fit efficiently on single high-performance GPUs, such as NVIDIA H200. Note: you must include detailed thinking on in the system prompt to enable reasoning. Please see Usage Recommendations for more.
Llama-3.3-Nemotron-Super-49B-v1 is a large language model (LLM) optimized for advanced reasoning, conversational interactions, retrieval-augmented generation (RAG), and tool-calling tasks. Derived from Meta's Llama-3.3-70B-Instruct, it employs a Neural Architecture Search (NAS) approach, significantly enhancing efficiency and reducing memory requirements. This allows the model to support a context length of up to 128K tokens and fit efficiently on single high-performance GPUs, such as NVIDIA H200. Note: you must include detailed thinking on in the system prompt to enable reasoning. Please see Usage Recommendations for more.
Compact Nemotron model for efficient reasoning and deployable AI agents
Mistral model for multilingual chat, reasoning, and tool-assisted workflows
Llama-3.1-Nemotron-Nano-8B-v1 is a compact large language model (LLM) derived from Meta's Llama-3.1-8B-Instruct, specifically optimized for reasoning tasks, conversational interactions, retrieval-augmented generation (RAG), and tool-calling applications. It balances accuracy and efficiency, fitting comfortably onto a single consumer-grade RTX GPU for local deployment. The model supports extended context lengths of up to 128K tokens. Note: you must include detailed thinking on in the system prompt to enable reasoning. Please see Usage Recommendations for more.
Compact Nemotron model for efficient reasoning and deployable AI agents