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DeepSeek v3: An advanced, open-source 671B parameter MoE AI language model offering state-of-the-art performance.
DeepSeek v3 represents a significant leap forward in the field of artificial intelligence, offering a powerful and versatile large language model (LLM) that rivals top-tier proprietary systems. This advanced model is built upon an innovative Mixture-of-Experts (MoE) architecture, featuring a massive 671 billion total parameters, with 37 billion activated for each token processed. This design allows for exceptional performance across a wide array of tasks while maintaining efficient inference capabilities.
Pre-trained on an extensive dataset of 14.8 trillion high-quality tokens, DeepSeek v3 possesses a comprehensive understanding of diverse domains, enabling it to excel in areas such as complex reasoning, sophisticated code generation, mathematical problem-solving, and multilingual communication. Its capabilities are further enhanced by a substantial , allowing it to process and comprehend lengthy inputs effectively, and for accelerated inference.
DeepSeek v3 utilizes a cutting-edge Mixture-of-Experts (MoE) architecture. This design activates a subset of 37 billion parameters per token from a total of 671 billion, optimizing performance and efficiency.
DeepSeek v3 is an invaluable asset for developers, researchers, and businesses seeking to leverage advanced AI capabilities. Whether you are building sophisticated applications, conducting cutting-edge research, or seeking to improve existing AI-driven products, DeepSeek v3 offers the power and flexibility to meet demanding requirements. Its open-source nature further democratizes access to high-performance AI, fostering innovation and collaboration within the global tech community. The model's versatility makes it suitable for a wide range of applications, from enhancing developer productivity with superior code generation to enabling more nuanced and context-aware AI interactions.","keyFeatures":[{"description:
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Pricing Model
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Utilizes an innovative Mixture-of-Experts (MoE) architecture with 671B total parameters, activating 37B parameters per token for optimal performance and efficiency.
Pre-trained on an extensive 14.8 trillion high-quality tokens, ensuring comprehensive knowledge across diverse domains and tasks.
Achieves state-of-the-art results across multiple benchmarks, including mathematics, coding, and multilingual tasks, surpassing many existing models.
Despite its massive scale, DeepSeek v3 maintains efficient inference capabilities through its innovative architecture design, making it practical for various applications.
Features a substantial 128K context window, enabling the model to process and understand extensive input sequences effectively for complex tasks.
Incorporates advanced Multi-Token Prediction techniques to enhance overall performance and accelerate inference speed.
