DeepSeek-Ai model with advanced reasoning capabilities and agent functions, combining high computational efficiency with GPT-5-level performance. Thanks to its Sparse Attention Architecture (DSA) and unique "in-call tool reasoning" mechanics, the model is ideally suited for building autonomous agents, ensuring a balance between speed, resource costs, and the complexity of tasks solved.
A specialized version of DeepSeek-V3.2 for deep reasoning, achieving GPT-5 and Gemini-3.0-Pro levels in solving complex problems in the fields of Olympiad mathematics and programming. The model does not support tool calling but possesses unlimited "thinking" depth, which allows it to achieve phenomenal results in these narrowly specialized knowledge domains. DeepSeek-V3.2-Speciale has become the first open model to win gold medals at the largest international mathematics and informatics Olympiads
DeepSeek-V3.2-Exp is an experimental model based on V3.1-Terminus, representing an intermediate step towards a next-generation architecture. The model incorporates DeepSeek Sparse Attention (DSA), a sparse attention mechanism that enhances the efficiency of training and inference in large-context scenarios. This model is a kind of snapshot of the current research being conducted by Deepseek-AI in its search for more efficient transformer architectures. According to test results, V3.2-Exp demonstrates performance comparable to the base version, with slight positive or negative dynamics on a number of benchmarks.
The updated version of the flagship model, DeepSeek-V3.1, demonstrates significant improvements: developers have achieved greater language consistency — the model now less frequently mixes Chinese and English and completely avoids generating random characters. In addition, the agents have been substantially enhanced — both Code Agent and Search Agent now deliver higher performance. To top it off, the model has shown noticeable gains across a range of key benchmarks.
A major update in DeepSeek-AI's LLM series, marking a significant step toward AI agent-oriented solutions. DeepSeek v3.1 is now a hybrid model supporting two intelligent modes (thinking/non-thinking), leading its class in accuracy and application flexibility. Performance improvements are evident across all benchmarks, with developers placing particular emphasis on enhanced tool usage efficiency. As a result, the model is ideally suited for complex analytical and research tasks, as well as enterprise-level agent systems.
DeepSeek-V3 0324 is an enhanced version of DeepSeek's powerful and popular MoE model with 685 billion parameters. Demonstrates exceptional quality, deep answer mining, and outstanding erudition in tasks ranging from analyzing complex legal documents to generating executable program code from scratch.
DeepSeek-V3 is a powerful MoE model with 671 billion parameters and 16 experts, one of the most popular open-source alternatives capable of competing with commercial analogs. With 128K tokens of context and high generation accuracy, it is ideal for professional tasks - from analyzing complex data to creating high-quality creative content.