Llama 3.3 Nemotron Super 49B v1 Model Overview Llama 3.3 Nemotron Super 49B v1 is a large language model (LLM) which is a derivative of Meta Llama 3.3 70B Instruct (AKA the reference model ). It is a reasoning model that is post trained for reasoning, human chat preferences, and tasks, such as RAG and tool calling. The model supports a context length of 128K tokens. Llama 3.3 Nemotron Super 49B v1 is a model which offers a great tradeoff between model accuracy and efficiency. Efficiency (throughput) directly translates to savings. Using a novel Neural Architecture Search (NAS) approach, we greatly reduce the model’s memory footprint, enabling larger workloads, as well as fitting the model on a single GPU at high workloads (H200). This NAS approach enables the selection of a desired point in the accuracy efficiency tradeoff. For more information on the NAS approach, please refer to this paper. The model underwent a multi phase post training process to enhance both its reasoning and non reasoning capabilities. This includes a supervised fine tuning stage for Math, Code, Reasoning, and Tool Calling as well as multiple reinforcement learning (RL) stages using REINFORCE (RLOO) and Onlin…
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