DeepSeek-V3-Base
| Property | Value |
|---|---|
| Total Parameters | 671B |
| Active Parameters | 37B |
| Context Length | 128K tokens |
| License | MIT (Code), Custom Model License |
| Paper | arXiv:2412.19437 |
What is DeepSeek-V3-Base?
DeepSeek-V3-Base is a groundbreaking Mixture-of-Experts (MoE) language model that represents a significant advancement in AI technology. With 671B total parameters and 37B activated parameters per token, it combines efficient architecture with innovative training approaches to achieve state-of-the-art performance while maintaining practical deployment capabilities.
Implementation Details
The model employs several cutting-edge technologies including Multi-head Latent Attention (MLA) and DeepSeekMoE architectures. It's trained on 14.8 trillion tokens using FP8 mixed precision training, making it the first model to validate FP8 training at such a massive scale. The training process was remarkably efficient, requiring only 2.788M H800 GPU hours.
- Auxiliary-loss-free load balancing strategy
- Multi-Token Prediction (MTP) objective
- FP8 mixed precision training framework
- 128K context window support
Core Capabilities
- Superior performance on math and coding tasks
- Strong multilingual capabilities, especially in English and Chinese
- Efficient inference with multiple deployment options
- Supports both commercial and research applications
- Exceptional performance on long-context tasks
Frequently Asked Questions
Q: What makes this model unique?
DeepSeek-V3-Base stands out for its innovative MoE architecture, FP8 training implementation, and remarkable efficiency in both training and inference. It achieves performance comparable to leading closed-source models while maintaining open-source accessibility.
Q: What are the recommended use cases?
The model excels in various applications including complex mathematical problems, code generation, multilingual tasks, and long-context processing. It's particularly effective for enterprise applications requiring high accuracy and efficiency.
