Qwen3.7-Plus is Alibaba's bid to turn multimodal AI into a full-blown autonomous agent

Eleven hours of autonomous app development

Using Qwen3.7-Plus, the team had a hybrid agent system build an English vocabulary learning app. According to Qwen, the agent ran for over eleven hours, producing more than 10,000 lines of code across more than 1,000 agent calls. The process covered requirements documentation, automated code generation, installation, test case creation, GUI-based testing, parallel test scenarios, and independent version management.

A second demo targets desktop apps: the agent reportedly recreated the native macOS Stocks app by operating it autonomously, parsing the UI structure, and generating SwiftUI code from it. It then connected an external API for real-time stock data, compiled the app, and ran ten functional tests on its own, including price lookups and search filters.

A third use case shows a browser agent via "Qwen for Chrome," a sidebar extension. With user permission, the model switches into agent mode and carries out tasks in a cloud console, like purchasing the cheapest available virtual server instance, including configuring the image, storage, and security groups. In a follow-up task, the agent also handles scaling and maintenance, Qwen says.

GUI tasks shine, hard reasoning tests don't

The benchmarks Qwen published paint a clear picture: the model excels at operating graphical interfaces. On AndroidWorld and ScreenSpot Pro, Qwen3.7-Plus sits well ahead of GPT-5.4 (xhigh), Opus 4.6 Max, and Gemini 3.1 Pro. It also leads on agent-oriented terminal work and long-horizon task planning.

On classic multimodal reasoning, results are mixed. Qwen3.7-Plus tops some visual reasoning tests but falls short of Gemini 3.1 Pro and GPT-5.4 on tougher scientific tasks like MedXpertQA-MM. On the text side, the team describes performance as on par with max-tier models, without beating them across the board.

Cross-framework compatibility sets it apart

Qwen3.7-Plus supports the Anthropic API protocol and works directly with Claude Code, OpenClaw, and Alibaba's own Qwen Code. The API also offers a feature called preserve_thinking that retains reasoning content from earlier conversation turns. The Qwen team explicitly recommends this setting for agentic tasks.

Beyond image processing, the model also covers video understanding and driving scene analysis, positioning it as a foundation for embedded systems and autonomous driving.

Qwen3.7-Plus is available through Alibaba Cloud Model Studio and, like its text-based sibling Qwen3.7-Max, is a proprietary offering with no open weights. Alibaba prices the Plus tier well below Max: Qwen3.7-Plus costs $0.40 per million input tokens and $2.40 per million output tokens, compared to $2.50 and $7.50 for Qwen3.7-Max. That makes Plus roughly six times cheaper on input and three times cheaper on output and well below the list prices of Western frontier models.