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Zhipu AI Launches GLM-5.3-Flash After Stealth Trial on 100,000 Domestic Chips

By Maria Santos
1 min read
Zhipu AI Launches GLM-5.3-Flash After Stealth Trial on 100,000 Domestic Chips
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Beijing-based Zhipu AI launched its open-weight model GLM-5.3-Flash on Wednesday after running the system across a cluster of 100,000 domestic Chinese chips. The release followed an unannounced trial on platforms including OpenRouter and OpenCode, where the system processed 62 trillion tokens under the test alias Ox Alpha before its formal unveiling.

Shares tied to the startup rose following the disclosure. Zhipu confirmed that the entire test deployment operated on domestic silicon rather than foreign hardware imports.

Traffic Across Developer Marketplaces

The stealth evaluation generated heavy traffic across international developer hubs over the past week. Users tested the then-unidentified Ox Alpha across code generation and complex task routing, driving sustained compute volume across the 100,000-chip array before Zhipu claimed ownership of the checkpoint.

Releasing the architecture as open weights allows enterprise clients and independent software developers to download, modify, and host the model on their own infrastructure. That deployment model lowers operating expenses for commercial software firms looking to integrate natural language tools without paying continuous per-token API charges to proprietary providers.

Domestic Compute Strategy

Building massive cluster capacity on domestic processors addresses direct supply constraints that Chinese technology groups face under ongoing hardware export restrictions. Large tech firms across the mainland have traditionally relied on foreign graphics processors to train top-tier foundation models, but local alternatives are now taking on larger workloads.

The performance of the 100,000-unit setup provides an operating template for other Chinese software developers seeking to decouple their deployment pipelines from foreign accelerators. Market attention now turns to downstream enterprise adoption rates and independent performance benchmarks against competing commercial models over the current quarter.

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