deepseek-ai/DeepSeek-V3

DeepSeek-V3 is built as a large-scale mixture-of-experts model, utilizing 671 billion total parameters while activating only 37 billion per token to maintain computational efficiency. Its architecture relies on Multi-head Latent Attention and the DeepSeekMoE framework, which were refined to balance inference speed with high-quality output. Designed to handle complex instructions, the model is engineered for scenarios requiring deep reasoning and reliable performance, making it a versatile tool for both standard text generation and intricate agent-based workflows.

The model underwent a rigorous training process involving 14.8 trillion high-quality tokens, followed by supervised fine-tuning and reinforcement learning stages to sharpen its capabilities. This lineage ensures stable performance across diverse tasks, from mathematical proving to logical verification. By integrating thinking processes directly into its tool-use capabilities and utilizing massive agent training data, the model is well-positioned for advanced research and practical applications that demand both precision and the ability to navigate complex, multi-step environments.