On June 15th, when the Hong Kong stock market opened, Zhipu AI's stock price surged continuously, reaching an intraday peak gain of 47.6%, setting a new record for single-day trading volume since its listing. By the close, the gain narrowed to 32.82%, with the total market capitalization surpassing HKD 649.6 billion.
The immediate catalyst came from two industry announcements two days prior.
On June 12th, due to U.S. government export control requirements, Anthropic suspended access to its latest flagship models, Claude Fable 5 and Claude Mythos 5. A day later, Zhipu announced that its latest open-source model, GLM-5.2, would be available to all Coding Plan users, with API access and model weights to be released the following week under the MIT license.
01 When the Most Advanced Models Become 'Potentially Unavailable'
On June 12th, Anthropic issued an official announcement stating that the U.S. government, exercising national security-related authority, issued an export control directive requiring the suspension of access to Claude Fable 5 and Claude Mythos 5 for all foreign nationals. The restrictions applied to foreign users both inside and outside the U.S., even including foreign employees within Anthropic.
Limited by the technical inability to accurately distinguish user nationality in real-time, Anthropic ultimately chose to temporarily disable the two models for all global customers to ensure compliance. This occurred only three days after the models' official release. As of now, both models are shown as unavailable on Anthropic's website, with no clear timeline for restoration.
As top-tier closed-source models in terms of current performance, the Claude series has been deeply integrated by numerous developers and enterprises for long-range tasks, code development, and complex document processing. The sudden service suspension directly disrupted many teams' workflows, sparking rapidly increasing discussions within the community about alternative solutions.
Just as the suspension news was gaining traction, on June 13th, Zhipu announced that its open-source flagship GLM-5.2 would be available to all Coding Plan users, covering Lite, Pro, Max, and Team editions. It also previewed that the API and model weights would be launched the following week, open-sourced under the MIT license.
In recent years, competition in the large model industry has primarily revolved around capability.
Whose reasoning is stronger, whose coding ability is better, who can first break through new capability boundaries—these factors almost dictated the choices of developers and enterprise customers.
However, the Anthropic incident highlights another issue previously often overlooked: beyond capability, whether a model can be accessed continuously and stably.
In this Anthropic event, for many developers and enterprises relying on overseas models for R&D work, even if they have accounts and paid subscriptions, they may face the risk of models suddenly becoming unavailable.
This is why this incident triggered far more discussion in the developer community than typical product updates.
As AI gradually evolves from a chat tool into infrastructure for software development, business operations, and even production processes, the stability, sustainability, and controllability of models are beginning to become metrics as crucial as model capability itself.
Zhipu stated in its announcement, "Cutting-edge intelligence should not belong only to a few, nor should it be subject to revocation by a few rules at any time." This statement, in essence, corresponds to the new reality facing the global AI industry today.
02 From 'Who is Stronger' to 'Who is More Accessible'
The capital market's swift reaction essentially represents an early pricing-in of this shift in industrial logic. Beyond the stock price performance, the market is more focused on the signals released by GLM-5.2 itself.
According to information disclosed by Zhipu, GLM-5.2 is its most capable open-source model to date, supporting a 1M context window and significantly enhancing long-horizon coding task capabilities. Zhipu positions it as a "truly usable 1M context" model, aiming to address the issue of models forgetting context during lengthy, multi-step engineering tasks.
A core keyword here is "Long Horizon Task." As AI Agents evolve from conversational tools into execution tools, models need to continuously handle thousands of tool calls, tens of thousands of lines of code, and large amounts of intermediate state information. The longer the context window, the stronger the model's ability to maintain project state and task continuity.
Current industry competition has shifted from "answering questions" to "sustained work." For developers, what truly matters is not parameter scale, but whether the model can maintain consistency and reliability over complex tasks lasting hours or even days.
Judging by the market reaction, investors have clearly recognized this change.
Oriental Securities pointed out in a research report that the Anthropic model incident exposed the risk of closed-source model access being subject to a single jurisdiction, which may drive more enterprises to shift their core AI capabilities toward domestic foundation models and localized deployment. Simultaneously, GLM-5.2 being open-sourced under the MIT license further lowers the barrier for enterprises to trial and integrate the model.
Over the past year, valuations assigned to large model companies by the capital market were largely based on model capability and market share. Today, as the global regulatory environment intensifies, a new valuation dimension is emerging—who can provide developers and enterprises with AI capabilities that are stable, sustainable, and reliably accessible in the long term.
When access to the world's most advanced models begins to be influenced by external factors, openness, accessibility, and autonomous controllability are becoming new bargaining chips in the AI competition.
