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In the hermetic corridors of Beijing’s tech district, where innovation smolders behind smoked-glass facades and venture capital flows like digital champagne, Zhipu AI has quietly unveiled its latest brainchild—an artificial intelligence agent that threatens to recalibrate our understanding of what machines can accomplish. AutoGLM Rumination, presented by CEO Zhang Peng at a Monday lunch affair with the understated drama that has become de rigueur for such announcements, represents not merely an incremental advance but rather a philosophical reimagining of AI’s relationship with human cognition and action.

This bifocal AI agent—at once a deep researcher and a pragmatic executor—situates itself at the contested boundary between thinking and doing, promising to fulfill the Cartesian dream of seamless transition from contemplation to action. The system balances three fundamental capacities: deep thinking, environmental perception, and tool manipulation—a tripartite structure reminiscent of classical philosophical models of mind.

The technical specifications, while typically relegated to the back pages of technical journals, here demand our attention. AutoGLM Rumination’s GLM-Z1-Air reasoning model performs the computational equivalent of an Olympic sprint, outpacing rival DeepSeek’s R1 by a factor of eight while consuming a mere three percent of the computational resources. One imagines the ghost of Claude Shannon smiling at such efficiency.

Unlike its competitors, which have embraced the subscription economy with the fervor of nineteenth-century railroad barons—Manus charges up to one hundred and ninety-nine dollars monthly for similar services—Zhipu has chosen to distribute AutoGLM Rumination freely through its official channels, including its website and mobile application. This decision suggests either remarkable confidence or strategic calculation in an increasingly competitive Chinese AI landscape.

The system’s capabilities extend beyond mere research. It conducts comprehensive web searches, arranges travel plans with the precision of a seasoned concierge, and crafts research reports that might pass muster in graduate seminars. More impressively, in its broader AutoGLM incarnation, the technology can navigate the digital embodiment of modern life—liking social media posts, executing e-commerce transactions, booking accommodations, purchasing train tickets, and ordering meals for delivery, all with operation logic that mimics human decision-making processes.

Recent upgrades have extended the system’s operational chain to fifty-four consecutive steps across multiple applications, suggesting a level of sustained attention that would exhaust many human operators. The system’s benchmark performance reportedly surpasses both OpenAI’s GPT-4o and Anthropic’s Claude 3.5 Sonnet in the Stanford-led AgentBench evaluations, particularly in tool-based execution, long-context reasoning, and browser automation—the holy trinity of contemporary AI agent assessment.

Zhipu AI, a spinoff from Tsinghua University founded in 2019, has quickly ascended the ranks of China’s AI firms, recently securing three consecutive rounds of government-backed funding in a single month. The company plans to release the core components of AutoGLM as open-source software on April 14th, an act of technological philanthropy that contrasts sharply with the proprietary instincts of many Western AI developers.

As digital assistants proliferate across our screens and speakers, AutoGLM Rumination raises the question of whether we are witnessing the birth of a new class of entity—one that thinks deeply but also acts decisively, blurring boundaries between tool and agent that have defined our relationship with technology since the Industrial Revolution. In the elegantly choreographed demonstration of AutoGLM’s capabilities, one glimpses not just an advanced software system but a potential collaborator in the ongoing human project of making sense of our increasingly complex world.