Why look beyond DeepSeek?
Because in the high-tech market, one breakout name is never the full story. The real story originates from knowing who else is building, competing, and growing for the same crown.
One name that’s making headlines lately is DeepSeek, a Chinese AI model gaining attention for its powerful language models.
But DeepSeek isn’t the only player in this advancing space. China’s AI scene is backed by serious funding and elite talent.
In this blog, we’ll look into the top 10 Chinese AI companies, like DeepSeek, that are influencing the global market.
Let’s get started.
How DeepSeek Grew Its Influence Over The Chinese Market?
Chinese startups and internet giants are in a constant competition with each other. With the emergence of DeepSeek’s low-cost, advanced open-source model, the Chinese market held a dominant position in this space.
Founded by a Hangzhou-based research lab in 2023, DeepSeek’s AI chatbot behaves and operates in a similar style to ChatGPT. This model was developed by Liang Wenfeng, co-founder of the Chinese quantitative hedge fund, High-Flyer Capital Management.
Since the release of DeepSeek’s advanced AI assistant, DeepSeek-V3 became the most downloaded app in global AI circles. This has overtaken rival AI platforms, including Silicon Valley titans like OpenAI and Anthropic, offering unrestricted usage at no cost.
| From The News “With the recent initial success of DeepSeek’s large language AI models, investors are grappling with concerns about potential AI price wars, Big 4’s AI capex intensity, and how to navigate investments across the various layers like enabling versus application layers.” UBS Group AG, January 27. Source: Investing.com |
The ‘Reasoning’ Capacity of DeepSeek
DeepSeek’s prominence demonstrated that a million-dollar budget or massive computing infrastructure isn’t always necessary for the development of any project. Its success proves how strategic thinking and an open-source ecosystem can rival the world’s top players.
The tech stack of DeepSeek is based on deep learning and large-scale language models. These models allow AI to handle complex prompts, simulate human-like conversations, and generate coherent responses across domains.
However, unlike a few competitors, DeepSeek, powered by V3, explains its reasoning potential before responding to queries. This transparency allows users to follow the AI’s logic step-by-step, turning it more interpretable and authentic.
| As Penned By Industry Experts “The company’s success is seen as a validation of China’s Innovation 2.0, a new era of homegrown technological leadership driven by a younger generation of entrepreneurs.” – Marina Zhang, Associate Professor, University Of Technology Sydney Source: BBC News |
Top Chinese AI Companies Like DeepSeek
- Doubao
Img: Doubao webpage screenshot
Released in January 2025, by a subsidiary of ByteDance (parent organization of TikTok), Doubao demonstrated amazing results with over 13 million users. This model was developed initially as a consumer-focused app for entertainment and personalized interaction.
However, with time, the spatial version of this model (Doubao 1.5 pro) was trained to support Chinese language fluency, cultural relevance, and vertical integration with other ByteDance properties like TikTok (Douyin), Toutiao, and Feishu.
On January 29th, Doubao’s most powerful version claimed it could outperform OpenAI’s version of o1 in specific tests. Despite all these extensive capabilities, ByteDance maintained a fair price for Doubao, which is half that of OpenAI.
Key Features
- Multimodal Capabilities of Doubao
ByteDance introduced multimodal capabilities, including document summarization, image analysis, speech, audio, and text-to-video features. The upgraded Doubao 1.5 Pro version also supports app integration via Feishu and Duoyin workstations.
- Friendly UI and One-Click Image Generation
Doubao’s interface divides different sections and scenarios for users, making it easy to use. Its heterogeneous design minimizes latency and is suitable for pre-fill decode operations, making it an efficient tool for balancing workload.
- Sparse MoE Architecture
To handle multi-turn reasoning, contextual memory, and task-specific outputs, Doubao uses reinforcement learning, reducing computational costs. With this, the model features a proprietary sparse MOU (mixture of experts) architecture, enhancing its reasoning abilities through an extensive ‘deep thinking’ mode.
➡ Primary MSP
Marketed as an ‘indispensable tool for work,’ Duobao delivers dense-model performance with just a fraction of activation load. This has created a benchmark for competitors like GPT-4o and Claude 3.5 Sonnet in coding, reasoning, knowledge generation, and Chinese language processing.
- GLM-4 Plus (ChatGLM)
Img: GLM4-Plus based Customer Service Bot
The recent ChatGLM language model, developed in August 2024 by Zhipu AI from Tsinghua University, is pre-trained on 10 trillion tokens to ensure better performance in coding and mathematical tasks.
This model utilizes PPO (Proximal Policy Optimization) technology to process multilingual data and further align it according to human feedback. In the multi-stage post-training process, the model undergoes supervised fine-tuning to execute complex multi-step tasks.
Backed by impressive performance metrics, GLM-Plus matched and exceeded top contenders like GPT 4-o, Gemini 1.5 Pro, and Claude 3 Opus.
Key Features
- Massive Multi-Task Language Understanding
GLM-4V 9B outperforms GPT-4 and other rivals in general metrics by maintaining strong conversational abilities in both Chinese and English. It can also generate and analyze high-resolution images (1120×1120), positioning it as a comprehensive ‘All tools’ module across technical and creative fields.
- Performance and Processing Power
This model demonstrates exceptional performance on key tests like MMLU, AlignBench, and MATH. It can also process long-text reasoning, almost up to 2 million Chinese characters, making it ideal for deep analysis and document summarization.
- Multilingual Conversational With Powerful Tool Integration
A unique feature of GLM-4-9B Chat is its multi-turn conversational coherence with memory retention, delivering human-like dialogue across extended sessions. This model also supports 26 languages for technical workflows and can execute the code, browse the web, and process up to 128k tokens.
➡ Primary MSP
The core MSP of GLM-4 lies in its task-specific tool integration, which enables autonomous tool selection. From executing code with an in-built Python interpreter to browsing the web as per the user’s intent, this model acts entirely as a versatile assistant across several domains
- Qwen 2.5- Max
Img: Qwen AI
On the first lunar new year holiday of January 2025, Alibaba Cloud released its latest and most advanced LLM, Qwen 2.5 Max. Built on the foundation of Qwen 2.0, this model showed effective performance in multiple arenas, outperforming models like Llama-3.1-405B, DeepSeek V3, and GPT 4o in several tests.
The model utilizes a MoE design, facilitating selective activation across layers without burning up enough computing power. Further, the model’s ability to toggle between natural conversation, structured-code output, and high-volume data analysis makes it one of the most versatile models released by China to date.
Key Features
- Advanced Functionality and Integration
The modular tool-use capabilities of Qwen 2.5 Max allow proper integration with APIs and third-party plugins. Also, the tool has massive datasets that Alibaba has fine-tuned through Supervised Learning and Human Feedback to adapt well with complex operational logic.
- Real-Time Explanation and Decision-Making
With explicit instruction tuning and structured output formatting, Qwen 2.5 Max can break down difficult topics in step-by-step format in real time. The model also provides multi-path justifications for nuanced user queries to perform high-end tasks like financial modeling or diagnostic troubleshooting.
- Multimodal Capabilities
The text-to-image generation feature of Qwen 2.5 Max positions the model as a reliable assistant in both analytical and creative visual workflows. Its visual-language element can interpret charts, forms, and annotated files. This alignment supports academic visuals, technical diagrams, document visual parsing, and OCR-style visual inputs.
➡ Primary MSP
The powerful balance of high performance and cost efficiency makes Qwen 2.5 Max perfect for product-scale deployments. So, with the ability to handle up to 128K tokens in a single session, it’s built for long-form reasoning, multi-document processing without compromising speed or authenticity.
- Tencent
Img: Tencent Holdings
The open-source model of Tencentb has made strides in AI. Primarily known for gaming and WeChat, this ubiquitous messaging app outperformed Meta’s Llama 3.1 across many factors.
However, its flagship model, Hunyuan-Large, was released in late 2024 with a total of 389 billion parameters, out of which 52 were activated at that moment. Tencent announced the first in the industry to adopt a hybrid architecture combining Mamba and Google’s Transformer.
Encouraging widespread adoption in the AI community and showcasing enterprise-grade intelligence, this model has made itself available on all developer-friendly platforms like HuggingFace and GitHub, delivering superior performance in all key areas.
Key Features
- Integrated Conversational Intelligence
Trained through interactive feedback, Hunyuan T1 in Tencent’s chatbot Yuanbao delivers coherent, long-form conversations across diverse topics. Combined with Tencent, T1 with context persistence across sessions allows smarter follow-ups and more personalized interactions.
- Reasoning Ability
Despite reduced resource demands, Hunyuan T1 achieves competitive results in reasoning and language understanding. Its capabilities are validated through consistent scores across AIME, MMLU pro, and C-Eval. These results confirm its viability as a well-rounded, high-accuracy, and general-purpose ready model for real-world reasoning applications.
- Large-Scale Reinforcement Learning
To optimize reasoning depth and response alignment with human intent, Hunyuan T1 uses large-scale reinforcement learning (RLHF). This approach replicates strategies used in DeepSeek-R1 and OpenAI’s o1; however, it is tuned specifically for social, enterprise, and entertainment use cases.
➡ Primary MSP
Hunyuan T1 stands out with its ability to continuously improve through live-user feedback. Integrated into Tencent’s AI service framework, it learns from real interactions across diverse use cases.
- Baidu (Ernie Bot)
Released on June 21, Ernie Bot v2.1.0 is a large language model powered by Ernie 3.5. It’s one of China’s leading search engine companies, significantly making strides in beta testing, surpassing ChatGPT 3.5 and outperforming GPT-4, as stated by China Science Daily.
As of late 2024, Ernie (Enhanced Representation through Knowledge Integration) was processing over 1.7 trillion tokens of text each and handling almost 1.5 billion daily calls, which marked a 30-fold increase from the previous year.
With strong performance in Chinese language processing, Ernie Bot represents Baidu’s core strategy to lead in AI-native infrastructure for enterprises and customers.
Key Features
- Plugin-Powered Versatility
Ernie 3.5’s built-in third-party plugin support extends beyond standard LLM capabilities. Tools like Baidu Search help with information retrieval, while the ChatFile plugin allows long-text summarization and Q&A. Baidu plans to open this plugin to external developers, making it a customizable AI platform for varied business needs.
- Knowledge Snippet Enhancement
A defining upgrade in ERNIE 3.5 is its Knowledge snippet enhancement, which analyzes queries and retrieves accurate information using knowledge graphs and search engines. These snippets generate content-rich prompts, improving factual accuracy and positioning Ernie as a knowledge-intensive application.
- Advanced Reasoning and Code Generation
With large-scale training on logical data, semantic layers, and symbolic neural networks, Ernie 3.5 has improved in mathematical reasoning and coding tasks. Baidu’s smart assistant tools, like Comate, can generate code using natural language and comments. These enhancements facilitate development, creative writing, and cross-domain implementation.
➡ Primary MSP
The strength of this knowledge-enhanced LLM is built on Baidu’s dual foundation of ERNIE and PLATO architectures. It blends core generative techniques like RLHF and supervised fine-tuning with proprietary advancements in layered integration that enable accurate, context-rich human-like outputs across applications.
- iFlyTek Spark
Img: iFlyTek Spark
The full-duplex voice interaction technology of iFlytek has established global competitiveness in ultra-anthropomorphic synthesis in Chinese, English, and other languages. It got standardized internationally in 2023 and leads the world in human-computer communication.
These technologies are demonstrated in iFlytek Spark V4, built on top of these new innovations, indicating the excellent far-field, multi-person, and real-time performance. The V3. 5Max edition released in May, had already surpassed GPT-4 Turbo 0429 in logic, math, and text generation.
Looking to the future, iFlytek plans to step up its R&D in high-noise, multi-speaker scenarios and cloud-edge integration to ensure it keeps its market competitiveness.
Key Features
- Technological Independence
iFLYTEK launched the Tideforce AI tool series, including industrial borescopes, acoustic imaging devices, and ultrasonic flaw detectors, all utilizing SPARK V4. 0. These are AI devices for applications in mission-critical sectors like aerospace, energy, and high-end manufacturing, slowly displaced by high-technology domestic and foreign inventions.
- Multilingual Digital Interaction
SPARK V4. 0’s multilingual transparent AI screen delivers live visual translation, a dual-sided display, and responses. This proves iFLYTEK’s ambition of becoming the pacesetter in cross-cultural, real-time digital communication. Also, the robot super brain platform supports multi-modal, multi-person interaction for next-level robotics and IoT implementations. These ultimately help extend the human potential of smart devices a bit further.
- Bridging the Gap in MedTech
The ’SPARK+Medical’ solution is the industry’s first AI general practitioner assistant to successfully pass China’s medical licensing exam. It offers smart diagnosis, Q&A, and public health education, all of which can help alleviate disparities in access to care, initiating a new era of AI-enabled patient-centred care.
➡ Primary MSP
As the backbone of Zhejiang’s smart education system, iFLYTEK SPARK V 4.0 powers next-gen solutions like Smart Blackboard, serving as an educational suite offering after-school support. This is the major reason for this model to stand out, changing the modern classroom experience.
- Megvii (Face++)
Img: Megvii Technology Limited
Founded in 2011, with headquarters in Beijing, Megvii (aka Face++) is one of China’s largest artificial intelligence firms, focusing on computer vision technology with a particular emphasis on facial recognition.
Though the firm is widely known for providing 70-odd Chinese cities with technology to help manage public security, its AI capabilities span healthcare, agriculture, and smart city planning.
With an emphasis on ‘AI for the real world,’ Megvii’s technology is integrated into all sorts of systems, from subway security scanners to facial authentication for civil services everywhere.
Key Features
- Facial Verification Across Platforms
Megvii’s FaceID Authentication Solution provides financial-level secure identity authentication through face comparison and live detection. Works with SDKs, mobile H5, PC web, and can support livestream ID verification, exams, fintech, and other use cases.
- Smart City Integration
Megvii’s AI infrastructure is embedded to provide access control, traffic monitoring, and civil authentication applications. It has been deployed in more than 80 Chinese cities to improve daily governance and public safety. Solutions extend from enterprise campuses to government buildings with real-time video analytics and identity verification.
- AI-Based Workspace
Megvii serves an ever-expansive developer workspace with its frameworks, namely, MegEngine and MegStudio, that help developers to deploy AI models. These are open-source frameworks, pre-trained models that contain modules that can be customized for real-world applications. This speeds AI adoption for myriad industries by providing production-ready, easy-to-use infrastructure.
➡ Primary MSP
Megvii operates under real-world constraints, including offline, on the move, or in harsh conditions. From rural sites with dodgy connectivity or hospitals requiring an instant diagnosis, these models are customized for low-latency, high-resiliency deployment. This makes Megvii a top choice for AI infrastructure in harsh, high-stakes, resource-scarce environments.
- MiniMax
Img: MiniMax
Launched in 2021, MiniMax is a growing AI company in China specializing in general-purpose foundation models in dialogue, reasoning, and multimodal content generation.
Its flagship product, Inspo, is a dialogue assistant that mixes natural conversation with the performance of a task, for consumer and enterprise use. Backed by significant support from Tencent, MiniMax focuses deeply on safety alignment, efficiency, and speed of deployment.
The company has established a solid foothold in China, where it focuses on high-performance models, designed to solve real-world problems across diverse verticals.
Key Features
- Multi-Agent Collaboration System
MiniMax has a layer for multiple AI agents to communicate, pass on work, and answer complex queries. This system is trialed for real-time settings such as customer service, supply chain, and education. In contrast to single-task LLMs, the architecture of MiniMax is designed to simulate collaborative intelligence. It’s a step toward creating distributed, specialized AI teams within one interface.
- LAFT Method
MiniMax applies a Lightweight adaptive fine-tuning (LAFT) technique to adapt user preferences. This allows ultra-fast personalization without increasing model bloat or performance. This system runs well on low-latency personalization for large-scale enterprise use cases or hybrid deployments.
- Code-Aware Language Framework
MiniMax silently made a code-native language model that learns the syntax and intent behind the code. This provides it with a decisive advantage in multi-language code generation and debugging hints to refactor legacy code bases. It’s piloted by a cohort of early adopters in fintech and developer tooling startups, making it well-suited to programming beyond shallow GPT outputs.
➡ Primary MSP
The model of MiniMax is optimized for ambiguity and mid-task pivots. That suggests it can predict user intent before the prompt is fully clear, especially useful in enterprise workflows and multi-turn conversations where clarity evolves gradually.
- WuDao 3.0
Img: WuDao 3.0
Developed by the Zhiyuan Research Institute, WuDao 3.0 is one of the largest open-source AI model families in China, with more than 1.75 trillion parameters. It comprises systems such as AquilaChat, AquilaCode, and some visual or multimodal systems.
With a capacity to understand multiple languages, code generation, image recognition, WuDao 3.0 is recognized for multi-discipline versatility, and its compatibility across chip architectures.
Made accessible for the scientific research community, this is also one of the efforts that showcase China’s determination to AI sovereignty and the shared benefits of the democratization of large model infrastructure to aid in academic and enterprise innovation.
Key Features
- AquilaChat Dialogue Models
There are 7B and 33B parameter versions of AquilaChat, and it is bilingual in English and Chinese, with 40% of its training data in Chinese. 7B model surmounts the performance of closed-source models internationally and domestically. It’s designed for fluent dialogue and bilingual context handling.
- AquilaCode Model
AquilaCode is a code generation model that uses logic-based prompts to generate programs. It can create everything from the simplest Fibonacci series to interactive games and sorting algorithms. Currently in development, it targets autonomous coding in multilingual environments.
- Wu Dao Vision Series
This suite features models such as EVA, EVA-CLIP, vid2vid-zero, and Painter, all of which work on a wide range of challenging visual AI tasks. EVA’s billion-parameter backbone leverages public data to learn image, video, and segmentation tasks with less supervision. It creates standards for how you visualize your data on the open-source platform.
➡ Primary MSP
WuDao 2.0 enabled Zhibing Hua, a virtual student who can write poems, draw paintings, and compose music. It is an example of WuDao’s unique capacity to blend language, vision, and generation in an integrated model. This legacy functionality makes AI Dungeon ideal for enterprises considering multimodal, culturally-aware creative AI.
- Kimi (Kimi k1.5)
Img: Kimi k1.5
Kimi k1.0 was developed by Moonshot AI and published on January 21, 2025. It is a multimodal large language model that takes as input both text and visual modalities (images and video). It’s intended for solving difficult problems in domains such as mathematics, coding, and multimodal reasoning.
Combining logical symbols and perceptual awareness, Kimi is your liquid sword when you need the power of perception to fulfill the intricate. Its flexible design means it’s applicable to everything from education and research to high-performance automation and interactive AI interfaces.
Key Features
- Dual CoT Reasoning Modes
Kimi k1. 5 is presented in two different modes: Long-CoT targets transparent, step-by-step thinking, whereas Short-CoT Clip aims for fast, high-accuracy results. This trade-off enables users to decide between interpretability and efficiency. It’s perfect for both enterprise workflows and developer use cases.
- Selective Training via Rejection Sampling
Instead of learning from all outputs, Kimi’s RL phase memorizes only the correct responses and prunes the erroneous reasoning paths. This ‘brutal but clean’ approach improves model accuracy without bloating the dimension of the total number of parameters. It approximates decision-making at the expert level, emphasizing the quality of outcome rather than the quantity of process.
- 128k Token Context with Real-Time File Handling
Kimi k1. 5, can read 128,000 tokens in processing, along with 50+ file uploads and live web search across 100+ websites. It is designed for deep, real-time research, and thus is incredibly useful in technical, legal, and data-heavy tasks.
➡ Primary MSP
The secret sauce behind Kimi is not getting hung up with token-level steps and, instead, learning to generalize across task modalities while maintaining chain-of-thought alignment via a hybrid training setup designed to optimize the output end’s quality, not the output tokens’ quality. Few competition models subscribe to a goal-first fine-tuning framework, so Kimi excels in high-stakes multi-step problem solving.
Detailed Comparison At A Glance: Top Chinese AI Companies
| Company Name | Model Name | Type Of Model | Strengths | Use Cases |
| DeepSeek | DeepSeek-VL | Code-Specialized and Vision-Language LLM | Exceptional performance in MATH, programming, and modal-reasoning. | Code generation, Software debugging, AI tutoring |
| ByteDance | Doubao | Chatbot/Multimodal LLM | Integrated with ByteDance, capable of fast Chinese language understanding | Document Q&A, Content creation, Douyin integration |
| Tsinghua KEG/Zhipu AI | GLM-4 | General LLM/Multimodal | GPT 4-o level strength, can process multilingual long-text(1M tokens) | Research, coding, and technical writing |
| Alibaba DAMO Academy | Qwen 2.5-Max | General LLM | An enterprise-grade tool with strong API support, facilitating high accuracy in code and reasoning | Enterprise automation, documentation, and data analysis |
| Alverse (360 Group) | Agibot | General LLM | Fine-tuned for enterprise compliance and customized for performing domain-specific tasks | Internal enterprise tool for education and daily productivity |
| Baidu | Ernie Bot | Multimodal LLM | Deep integration with Baidu search facilitates vision and text capabilities | Search-enhanced tasks, knowledge retrieval, and document summarization |
| iFlyTek | Spark | Conversational/Education-focused | Chinese teaching support, having multimodal integration and speech recognition capability | Speech-to-text, academic tutoring, and test preparation |
| Megvii | Face++LLM | Vision-first LLM | Computer vision supporting video analytics with identity recognition and language fusion | Security, surveillance, and facial recognition |
| MiniMax | Minimax LLM | Conversational/Consumer-focused | High-speed inference and app integration | Social AI, digital chatbot apps, |
| Beijing Academy of AI | WuDao 3.0 | Super-scale LLM(1.75T parameters) | Chinese knowledge base for general performance | Policy modeling, academic research, and simulations |
| Moonshot AI | Kimi (Kimi K1.5) | Chatbot/Long-Context focused | User-friendly interface, 2M token context for fluent long-text summarization | Legal research, customer support, and academic analysis |
Why Is China Catching Up So Fast in the AI Race?
China invested approximately $132.7 billion in AI development between 2019 and 2023. During this period, Chinese AI startups experienced rapid growth and significant investment from both the government and private sectors.
- A Focus On Open Source and Academic Power
China’s gains in AI are marked by major universities like Peking University and Tsinghua University, where 47% of top AI researchers have pursued their undergraduate courses in AI and related fields.
Further, the GML and WuDao models were launched by academic-industry symbiosis, bypassing Western countries’ ‘Black Box’ approach. This intellectual openness generated a decentralized idea, defying conventional paradigms.
- A Long-Term Vision and Government Support
China’s AI development programme follows a 3-phase national strategy (2017-2030) to ensure sustained support for AI across sectors and regions. This proactive, multilevel policy ensures cohesive national growth with a preemptive roadmap.
As China aims to position itself as a global leader in AI theory, technology, and application by 2030, central and local governments coordinate to provide initiatives like subsidized AI chips and regional AI clusters.
- Near-Parity in Model Performance
Chinese AI models are now popular in leading Western counterparts, achieving near-parity in areas like reasoning, coding, and multimodal capabilities. Experts also note that Chinese AI models are competitive, and sometimes superior, proving the nation’s capacity for high-tech innovation.
Hence, the point of ‘lagging behind’ has already been banished in China, as Chinese teams have won top prizes at International competitions such as the Large Scale Visual Recognition Challenge, and have added these advances into their domestic applications.
Conclusion
The AI space is quite broad, not built on a one-size-fits-all foundation. Each application, from NLP to code generation or advanced AI/ML techniques, requires a distinct set of capabilities.
A solution that excels in one domain might be a suboptimal choice for the other. That’s why a clear understanding of emerging Chinese AI startups like DeepSeek is essential for making technically sound decisions.
Hence, as these companies continue to grow, keeping them on your radar isn’t just smart, but necessary to understand the subtle strengths of each AI platform and how they align with the real-world needs.
