The document details DeepSeek-V3, a 671B-parameter Mixture-of-Expert large language model. It covers the model's architecture, including Multi-Head Latent Attention and an innovative auxiliary-loss-free load balancing strategy for DeepSeekMoE. The training process, encompassing pre-training on 14.8 trillion tokens and post-training using supervised fine-tuning and reinforcement learning, is described. Extensive evaluations demonstrate DeepSeek-V3's strong performance across various benchmarks, surpassing many open-source and achieving results comparable to leading closed-source models. Finally, the document explores infrastructure optimizations, including an FP8 mixed-precision framework, and suggests improvements for future AI hardware design.

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DeepSeek-V3 Documentation: GitHub

Deepseek-V3 Download : GitHub