Alibaba Cloud Coding Plan Now Supports Qwen 3.5, GLM-4.7, Kimi-K2.5 and More

Alibaba Cloud's Coding Plan subscription has expanded its model lineup with Qwen 3.5-Plus, GLM-4.7, and Kimi-K2.5, allowing subscribers to switch freely between models under one subscription.

The service is compatible with mainstream AI coding tools including Qwen Code, Claude Code, Cline, and OpenClaw, enabling developers to leverage multiple cutting-edge models without switching environments.

阿里云Coding Plan支持千问3.5、GLM-4.7、Kimi-K2.5等模型-36氪

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阿里云Coding Plan支持千问3.5、GLM-4.7、Kimi-K2.5等模型

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36氪获悉，阿里云Coding Plan订阅服务上新Qwen 3.5-Plus、GLM-4.7、Kimi-K2.5等编程模型，用户订阅后即可自由切换模型。用户可在Qwen Code、Claude Code、Cline、OpenClaw等主流AI工具使用阿里云Coding Plan订阅服务。

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In-Depth Analysis and Industry Outlook

From a broader perspective, this development reflects the accelerating trend of AI technology transitioning from laboratories to industrial applications. Industry analysts widely agree that 2026 will be a pivotal year for AI commercialization. On the technical front, large model inference efficiency continues to improve while deployment costs decline, enabling more SMEs to access advanced AI capabilities. On the market front, enterprise expectations for AI investment returns are shifting from long-term strategic value to short-term quantifiable gains.

However, the rapid proliferation of AI also brings new challenges: increasing complexity of data privacy protection, growing demands for AI decision transparency, and difficulties in cross-border AI governance coordination. Regulatory authorities across multiple countries are closely monitoring these developments, attempting to balance innovation promotion with risk prevention. For investors, identifying AI companies with truly sustainable competitive advantages has become increasingly critical as the market transitions from hype to value validation.

From a supply chain perspective, the upstream infrastructure layer is experiencing consolidation and restructuring, with leading companies expanding competitive barriers through vertical integration. The midstream platform layer sees a flourishing open-source ecosystem that lowers barriers to AI application development. The downstream application layer shows accelerating AI penetration across traditional industries including finance, healthcare, education, and manufacturing.