ZhiJiu Builds Industry's First L4 10,000-Card Cluster, Autonomous Driving Enters New Paradigm of Multimodal Large Models
ZhiJiu announced the completion of the industry's first L4-level 10,000-card cluster, with a total scale of nearly 15,000 cards, to support its APEX multimodal foundation large model's evolution from tens of billions to hundreds of billions of parameters, driving autonomous driving into a new paradigm of multimodal large models.
Key Takeaways
- Key Highlight：ZhiJiu announced the completion of the industry's first L4-level 10,000-card cluster, with a total scale of nearly 15,000 cards, to support its APEX multimodal foundation large model's evolution from tens of billions to hundreds of billions of parameters, driving autonomous driving into a new paradigm of multimodal large models.
- Innovation & Tech：Highlights advancements in ZhiJiu, Builds, Industry, demonstrating rapid progress in model capabilities.
- Industry Impact：Reported via 雷峰网 (CN), offering actionable signals for developers and technology leaders.
ZhiJiu recently announced a strategic upgrade to "city-level physical AI" and disclosed that it has built a computing cluster with a total scale of nearly 15,000 cards. The completion of this underlying computing infrastructure marks a new magnitude in R&D resource investment for L4-level autonomous driving teams, providing solid computing power guarantees for processing massive amounts of complex urban road condition data.
Behind the 10,000-card cluster is the APEX multimodal foundation large model that ZhiJiu is currently developing. The model is evolving from tens of billions of parameters to hundreds of billions of parameters, indicating that the core of autonomous driving technology is gradually shifting toward multimodal large models. Enhancing vehicles' perception and decision-making capabilities in the complex physical world through large models has become a key technical route for the second half of autonomous driving.
This technological upgrade breaks the industry's inherent bias that urban freight autonomous vehicle technology barriers are relatively low. As an early pioneer in the autonomous driving field, ZhiJiu aims to establish a higher technological moat in scenarios such as urban distribution logistics and improve the generalization capability of autonomous driving systems by building large-scale computing power and self-developed large models.
From an industry perspective, autonomous driving entering the new paradigm of multimodal large models means that computing power reserves and model scale will directly determine a company's core competitiveness. As more companies join the large model camp, the computing power arms race and technological iteration in the autonomous driving industry are expected to further accelerate.
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Industry Insights & Analysis
As artificial intelligence rapidly evolves, breakthroughs surrounding ZhiJiu, Builds, Industry, First are shifting toward scalable, robust real-world implementations.
Driven by both open-source ecosystems and proprietary model architectures, the integration between compute optimization, data engineering, and agentic workflows is accelerating. This development provides a strategic benchmark for upcoming AI tooling and developer workflows.