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Can low-precision training match BF16 accuracy at scale? 

To validate the practical impact of low-precision training for real-world large-model pretraining, the team evaluated both the training convergence and downstream task performance across two widely used dense transformer architectures: Llama 3 8B and an NVIDIA internal research 8B model (Research-8B with dense grouped query attention (GQA) architecture that is similar to Llama 3 8B). The models were trained on 1 trillion tokens.

Using NVFP4 Low-Precision Model Training for Higher Throughput Without Losing Accuracy | NVIDIA Technical Blog