Introduction to Chinese Open Agentic Models
China has emerged as a leader in the development of open-source large language models, particularly in the realms of agentic structures and profound reasoning capabilities. With advancements that rival other global technologies, this guide delves into the best Chinese open agentic and reasoning models as of 2025, highlighting their strengths, applications, and unique features.
Kimi K2 (Moonshot AI)
Profile: Utilizing a Mixture-of-Experts architecture, Kimi K2 boasts an impressive context capacity of up to 128K tokens and is fluent in both Chinese and English.
Strengths: It excels in reasoning, coding, and handling long documents, with well-rounded agentic skills that include tool usage and multi-step automation.
Use Cases: Kimi K2 is ideal for general-purpose agentic workflows, document intelligence, code generation, and applications that require multilingual capabilities.
GLM‑4.5 (Zhipu AI)
Profile: This model features 355 billion parameters with a native agentic design and long context support.
Strengths: GLM‑4.5 is purpose-built for complex agent execution and has amassed a community of over 700,000 developers.
Use Cases: It’s particularly useful for multi-agent applications and cost-effective autonomous agents.
Qwen3 / Qwen3-Coder (Alibaba DAMO)
Profile: A next-gen intelligent model that supports dynamic reasoning and specializes in multilingual coding across 119+ languages.
Strengths: It can switch between different thinking modes, achieving high scores in coding and tool usage.
Use Cases: Great for global SaaS applications and teams focused on complex coding tasks.
DeepSeek-R1 / V3
Profile: Recognized for its reasoning-first approach, DeepSeek offers multi-stage reinforcement learning with substantial parameters dedicated to each query.
Strengths: Its performance in logical reasoning surpasses many competitors, especially in scientific tasks.
Use Cases: Especially beneficial for technical and scientific research requiring high interpretability.
Wu Dao 3.0 (BAAI)
Profile: A modular model that combines strong long-context processing with multimodal capabilities, suitable for both text and images.
Strengths: It supports multilingual workflows, making it ideal for startups and lower-compute environments.
Use Cases: Perfect for multimodal deployment and flexible application development.
ChatGLM (Zhipu AI)
Profile: Designed for edge-ready applications, ChatGLM provides bilingual support and can manage context windows of up to 1 million tokens.
Strengths: It stands out in on-device applications focusing on long-document reasoning.
Use Cases: Particularly useful for local government initiatives and environments where privacy is crucial.
Manus & OpenManus (Monica AI / Community)
Profile: These models represent a new benchmark for autonomous reasoning and real-world tool use.
Strengths: They show natural behavior in various applications, including web search and voice commands.
Use Cases: Best for tasks requiring mission-completion agents and orchestration among multiple agents.
Doubao 1.5 Pro
Profile: Known for its logical reasoning structures and high context window exceeding 1 million tokens.
Strengths: It provides real-time problem-solving capabilities, making it suitable for scalable enterprise environments.
Comparative Summary of the Leading Models
| Model | Best For | Agentic? | Multilingual? | Context Window | Coding | Reasoning | Unique Features |
|---|---|---|---|---|---|---|---|
| Kimi K2 | All-purpose agentic | Yes | Yes | 128K | High | High | Mixture-of-Experts |
| GLM-4.5 | Agent-native applications | Yes | Yes | 128K+ | High | High | Native task API |
| Qwen3 | Control, multilingual | Yes | Yes (119+) | 32K–1M | Top | Top | Fast mode switching |
| DeepSeek-R1/V3 | Reasoning/math/science | Some | Yes | Large | Top | Highest | RLHF training |
| Wu Dao 3.0 | Modular, multimodal | Yes | Yes | Large | Mid | High | Text/image, modular builds |
| ChatGLM | Edge/mobile agentic use | Yes | Yes | 1M | Mid | High | Resource-efficient |
| Manus | Autonomous agents | Yes | Yes | Large | Task | Top | Real-world AGI |
| Doubao 1.5 Pro | Logic-heavy enterprise | Yes | Yes | 1M+ | Mid | Top | Logic structure |
Conclusion: Selecting the Right Model
Choosing the right open agentic model depends on your specific needs. For a balanced, all-around solution, Kimi K2 stands out effectively. If you require sophisticated task automation, GLM-4.5 is your go-to. For enterprises addressing multilingual demands, Qwen3 and Qwen3-Coder offer remarkable capabilities. Meanwhile, DeepSeek-R1/V3 excels in research for logic-intensive tasks. Wu Dao 3.0 is perfect for smaller projects requiring versatile multimodal approaches. Finally, for sector-specific deployments, consider the offerings from Doubao and the other “Six Tigers.” Each model contributes uniquely to the expanding landscape of AI, providing various options for businesses and developers alike.
FAQ
- What are the key features of agentic models? They focus on reasoning, tool use, and process automation, allowing for intelligent task execution.
- How do the context windows vary across models? Context windows can range significantly, from 32K to over 1M tokens, allowing for various levels of textual complexity.
- What industries can benefit from these models? Various sectors, including tech, finance, and healthcare, can leverage these models for improved efficiency and automation.
- Which model is best for multilingual applications? Qwen3 is highly regarded for its multilingual capabilities, supporting over 119 languages.
- Can these models be used in startups with limited resources? Yes, models like Wu Dao 3.0 are designed for lower-compute environments, making them accessible for startups.
