6 Chinese AI Models: DeepSeek vs Kimi vs GLM vs Qwen vs MiniMax vs MiMo!
The video compares six Chinese AI models — DeepSeek, Kimi, GLM, Qwen, MiniMax, and MiMo — tested against the same coding prompt to reveal their strengths. Each model is shown to have a distinct specialty, from deep reasoning and research to clean code generation and agentic planning. The presenter argues that Chinese AI is no longer a niche trend but a serious competitive force reshaping the global AI landscape.
Summary
The video presents a side-by-side evaluation of six Chinese AI models: DeepSeek, Kimi, GLM, Qwen, MiniMax, and MiMo. The presenter, a digital avatar for Julian Goldie, frames the video around a single coding task — building a simple to-do app — applied consistently across all six models to produce comparable, real-world results rather than relying on benchmark charts or marketing claims.
DeepSeek is highlighted first as the most well-known of the six. Its latest version, DeepSeek V4, features a 1 million token context window and notably runs on Huawei chips rather than Nvidia hardware, signaling China's growing ability to develop frontier AI without Western semiconductor dependency. In the coding test, DeepSeek produced structured, logical code using step-by-step reasoning, making it the presenter's top pick for complex problems and long document tasks.
Kimi, from Moonshot AI (version K2.5), is positioned as the research-oriented model. It excels at processing large documents, maintaining memory across long conversations, and explaining reasoning behind outputs. In the coding test, Kimi provided more contextual explanation around its code rather than the tightest output, making it better suited for learners or research-heavy workflows than for raw coding speed.
GLM, developed by Zhipu AI (versions GLM-5 and GLM-4.7), is described as a coding-first model that surprised the presenter with the cleanliness and professionalism of its output. The code felt like it was written by a senior developer, with strong naming conventions and minimal unnecessary content. GLM also has a well-developed API ecosystem, making it practical for product development despite receiving less global attention than DeepSeek.
Qwen, built by Alibaba (versions Qwen-3 and Qwen-3.5), uses a mixture-of-experts architecture for high efficiency with lower compute requirements. It produced what the presenter called the cleanest code output of all six models — properly structured, readable, and free of unnecessary elements. Qwen's growing open-source community adds further appeal for developers and builders.
MiniMax (versions M2.5 and M2.7) stood out for its agent-oriented design. Unlike the others, it did not immediately write code in response to the prompt — it first planned the task, broke it into steps, and reasoned through the architecture before generating the solution. The presenter views this agentic, multi-step reasoning capability as the most forward-looking feature among the six models.
MiMo is described as the least-known but fastest-rising model on the list. It does not specialize in any single area but aims for balanced, reliable performance across diverse tasks. Despite being less prominent, it competes on major benchmark leaderboards alongside models backed by much larger resources, which the presenter uses as evidence of the broader momentum in Chinese AI development.
The video closes with a broader argument: AI is no longer dominated by a small set of Western players. China is releasing open, rapidly iterating models that are gaining millions of users and pushing the entire industry forward. The presenter warns that ignoring these models means falling behind, as they are free to use, openly available, and improving weekly.
Key Insights
- The presenter claims DeepSeek V4 runs entirely on Huawei chips rather than Nvidia hardware, arguing this represents a major strategic shift showing China can build top-tier frontier AI without any Western semiconductors.
- The presenter argues Qwen produced the cleanest code output of all six models tested, attributing this to its mixture-of-experts architecture which delivers strong results with less compute than conventional models.
- The presenter highlights MiniMax as uniquely different because it planned and broke the to-do app task into architectural steps before writing any code — behavior he describes as agent-style reasoning that enables handling far more complex work than one-shot coding.
- The presenter describes GLM's coding output as feeling like it was written by a senior developer rather than an AI, noting clean structure, good naming conventions, and minimal fluff, while pointing out it has a strong API ecosystem for product builders despite low global hype.
- The presenter argues that six months ago most people had not heard of half these models, but they are now appearing on every major benchmark leaderboard and gaining millions of users, framing China's AI output as 'the new reality' rather than a passing trend.
Topics
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