Compute-Efficient Pretraining Techniques for Large-Scale Language Models

Magic Team reports a 10x increase in pretraining compute efficiency, achieving performance comparable to DeepSeek V4 Pro with 50x fewer FLOPs. Their method outperforms open-source models on perplexity and reasoning tasks, enabling cost-effective scaling for AI research and development.

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