DeepSeek has open-sourced DeepSeek-V3, an advanced Mixture-of-Experts (MoE) language model boasting 671 billion parameters and trained on 14.8 trillion tokens. This model introduces significant enhancements over its predecessor, including a novel load balancing strategy and a Multi-Token Prediction (MTP) objective, alongside utilizing mixed-precision training techniques. DeepSeek-V3 outperformed several baseline LLMs across key benchmarks, though it still faces some deployment challenges. The model’s architecture allows for only a fraction of parameters to be active during inference, ensuring efficiency.
DeepSeek-V3, a 671B parameter MoE LLM, surpasses other open-source models on major benchmarks thanks to extensive training and improved architecture.
With the introduction of a new load balancing strategy and Mixed-Precision methods, DeepSeek-V3 achieves enhanced performance while maintaining efficiency in training.
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