As MiniMax's flagship agentic model, it features exceptional self-evolution and complex engineering capabilities. Deeply integrated with the Agent Harness framework, it excels in software engineering delivery, complex reasoning, and automated office document processing, serving as a core engine for high-level AI agent applications.

A high-compute model specifically engineered for deep reasoning and complex logical analysis. Leveraging DeepSeek Sparse Attention, it excels in mathematical, algorithmic, and research-grade tasks. Optimized through extensive reinforcement learning, it offers exceptional performance on long-context scenarios, making it an ideal choice for academic exploration and solving highly complex problems.

A high-performance foundation model developed by 01.AI, featuring excellent multilingual understanding and logical reasoning capabilities. It supports a 200k long context window, enabling efficient handling of long-document analysis, deep reading comprehension, and large-scale knowledge retrieval tasks, providing robust support for complex and massive data processing while maintaining performance on shorter inputs.

A high-performance multilingual text embedding model supporting long-context processing up to 8,192 tokens. It utilizes LoRA adapters to provide task-specific embeddings for retrieval, clustering, and classification, while supporting Matryoshka representation learning for flexible dimensions, making it an ideal foundation for large-scale semantic search and RAG systems.

Doubao Seed 2.0 Mini is ByteDance’s lightweight general-purpose language model designed for low-latency and cost-efficient text understanding and generation. It supports conversational interaction, content drafting, basic reasoning, information extraction, and common coding tasks. The model is well suited for AI assistants, enterprise Q&A, lightweight workflow automation, and large-scale text processing scenarios where responsiveness and efficiency are important.

A flagship professional-grade image generation model, excelling in complex text rendering and layout design. It delivers photorealistic quality with precise material and texture reproduction, making it an ideal choice for posters, product imagery, and commercial creative workflows.

As Anthropic's most capable Sonnet model to date, this version delivers a full upgrade across coding, computer use, and agentic planning. With advanced reasoning capabilities and a 1M token context window, it excels at long-document analysis, complex codebase maintenance, and automated workflows, making it the ideal choice for balancing high performance with productivity.

As the flagship model of the Doubao family, this version is deeply optimized for multimodal agent scenarios. It possesses exceptional complex instruction following and deep reasoning capabilities, efficiently processing text, image, and video inputs. With enhanced visual understanding and tool-calling capabilities, the model leads in task planning and logical execution, making it ideal for the development and deployment of enterprise-level agents that require complex logical analysis and multimedia content comprehension.

A high-performance reasoning-enhanced large language model that significantly improves logical reasoning, mathematical proof, and code generation capabilities through reinforcement learning. This version optimizes depth of thought and supports structured output and function calling for complex tasks, offering deep reasoning processes while reducing hallucinations for demanding technical applications.

qwen-mt-turbo is a high-performance machine translation model in the Alibaba Cloud Qwen family, designed for multilingual text translation and cross-language communication. It focuses on balancing translation quality, speed, and cost efficiency, making it suitable for stable translation of short to medium-length text. Typical use cases include product internationalization, content localization, cross-border e-commerce, customer support, and document translation workflows.