DeepSeek, a rapidly growing Chinese AI startup, employs several strategies to effectively manage large-scale token requests, particularly through its latest model, DeepSeek-V3. This model utilizes a Mixture-of-Experts (MoE) architecture, which allows it to selectively activate a subset of parameters for each token processed. Specifically, DeepSeek-V3 has a total of 671 billion parameters, but only 37 billion are activated for each token during inference. This design significantly enhances computational efficiency compared to traditional dense models, where all parameters are engaged for every request[1][4].
To further optimize performance, DeepSeek-V3 implements an effective load balancing strategy throughout its training and inference processes. This approach ensures that no tokens are dropped during either phase. The model maintains a good load balance by utilizing a restricted routing mechanism that limits communication costs and allows for nearly full computation-communication overlap. As a result, DeepSeek-V3 can handle high volumes of token requests without sacrificing performance or reliability[2][4].
In terms of training, DeepSeek-V3 is pre-trained on an extensive dataset comprising 14.8 trillion tokens, followed by stages of supervised fine-tuning and reinforcement learning to refine its capabilities. The training process is designed to be stable and efficient, completing in less than two months with a total cost of approximately $5.576 million in GPU hours[1][2]. This efficient use of resources allows DeepSeek to scale effectively while managing large-scale token requests across its services.
Overall, DeepSeek's innovative architecture and strategic approaches enable it to handle substantial token requests efficiently, making it a competitive player in the AI landscape.
Citations:
[1] https://thehackernews.com/2025/01/top-rated-chinese-ai-app-deepseek.html
[2] https://arxiv.org/html/2412.19437v1
[3] https://protos.com/chinese-openai-rival-deepseek-limits-signups-after-large-scale-attack/
[4] https://encord.com/blog/deepseek-ai/
[5] https://www.techtarget.com/whatis/feature/DeepSeek-explained-Everything-you-need-to-know
[6] https://www.reddit.com/r/LocalLLaMA/comments/1hzkw3f/deepseek_v3_is_the_gift_that_keeps_on_giving/
[7] https://www.cnbc.com/2025/01/27/deepseek-hit-with-large-scale-cyberattack-says-its-limiting-registrations.html
[8] https://daily.dev/blog/deepseek-everything-you-need-to-know-about-this-new-llm-in-one-place