The Week China Open-Sourced The Frontier

In a 48-hour span on February 11-12, 2026, three Chinese AI laboratories independently released frontier-class language models under open licenses. Not research demos — full production models matching or exceeding GPT-5.2 and Claude Opus 4.5 on major benchmarks. Three labs, three architectures, all open-weight, all arriving at the same conclusion: sparse Mixture of Experts is the path to frontier AI that anyone can run. This episode breaks down what each lab built, who built it, and why it matters for the future of open-source AI.

StepFun — The Efficiency King

StepFun released Step 3.5 Flash on February 11th — a 196 billion parameter sparse MoE model that activates just 11 billion parameters per inference. That means frontier-level intelligence running on a Mac Studio. The 45-page arXiv paper introduces MIS-PO, a novel reinforcement learning algorithm for stable off-policy training at scale. Step 3.5 Flash scores 97.3% on AIME 2025 and delivers 100-350 tokens per second via multi-token prediction. It's the only model of the three with a full technical report — StepFun published the recipe, not just the weights.

StepFun Researchers

StepFun was founded by three former Microsoft veterans. CEO Jiang Daxin served as Vice President and Chief Scientist at Microsoft's Software Technology Center Asia. The name that stands out is Harry Shum (Heung-Yeung Shum), former Executive Vice President of AI and Research at Microsoft — one of the highest-ranking Chinese executives in American tech history. Shum ran Microsoft Research Asia, the lab that trained an entire generation of Chinese AI leaders including the founders of DeepSeek, SenseTime, and Megvii. He studied under Turing Award winner Raj Reddy at Carnegie Mellon. Other key contributors include Jiao Binxing and Zhu Yibo.

MiniMax — The Cost Destroyer

MiniMax released M2.5 on February 12th with a pitch of "intelligence too cheap to meter." At $0.15 per million input tokens, M2.5 costs one-twentieth what Claude Opus charges. The 230 billion parameter model activates roughly 10 billion parameters and scores 80.2% on SWE-bench Verified — within 0.7% of Claude Opus 4.5. MiniMax built Forge, an agent-native reinforcement learning framework with over 200,000 real-world training environments, and during training the model spontaneously began writing specification documents before coding. Two variants ship: M2.5 standard at 50 tokens per second and M2.5-Lightning at 100 tokens per second.

MiniMax Researchers

MiniMax was founded by Yan Junjie, who earned his PhD in AI at 25, became VP of SenseTime at 27, founded MiniMax at 31, and became a billionaire at 36 after MiniMax's Hong Kong IPO in January 2026. He holds roughly 200 academic papers with 30,000 citations and serves as both CEO and CTO — the only leader among these three labs wearing both hats. His vision of commoditized AI comes directly from deploying computer vision at massive scale at SenseTime. Key team members include Yang Bin and Zhou Yucong.

Zhipu AI — The Geopolitical Bombshell

Zhipu AI (trading as Z.AI) released GLM-5 on February 11th — a 744 billion parameter model trained entirely on Huawei Ascend 910 chips. Zero NVIDIA hardware. Zhipu is on the US Commerce Department's Entity List, and they just trained the largest open-weight model of the three on domestic silicon. GLM-5 holds the #1 score on BrowseComp (75.9) across all models, open or closed. Before the official launch, Zhipu stealth-tested GLM-5 as "Pony Alpha" on OpenRouter, letting users benchmark it blind. The company IPO'd on the Hong Kong Stock Exchange on January 8th, raising $558 million — the first publicly traded foundation model company in the world.

Zhipu AI Researchers

Zhipu was founded by Tang Jie, professor at Tsinghua University and ACM Fellow who invented the GLM (General Language Model) architecture. He designed the original GLM in his lab, trained it at the Jinan Supercomputing Center, then commercialized it. Co-founder Li Juanzi, also a Tsinghua professor, is an expert in knowledge graphs and factual reasoning — her work is directly reflected in GLM-5's record-low hallucination rate. Zhang Peng rounds out the core leadership. Zhipu AI is essentially Tsinghua's computer science department, commercialized.

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