Alibaba-affiliated companies are intensifying their presence in the consumer market, marked by the recent launch of LingGuang, an artificial intelligence assistant introduced by Ant Group on November 19. LingGuang distinguishes itself by providing multimodal responses, generating interactive webpages that include images, text, 3D models, animations, maps, tables, and audio or video, rather than limiting interactions to plain text.
The assistant enables users to input natural language commands, allowing it to create editable, interactive mini apps in approximately 30 seconds. This app supports a variety of output formats, enhancing user engagement and utility. Another feature of LingGuang functions as a visual assistant, enabling real-time photo uploads that the AI interprets to provide pertinent information or perform follow-up tasks.
By November 24, just five days post-launch, LingGuang had already surpassed one million downloads, ranking sixth on app store charts. This rapid uptake outstripped that of several established AI applications, notably Sora 2, which took five days to achieve the same milestone, according to mobile analytics firm Appfigures.
This surge in consumer-focused AI initiatives follows Alibaba’s decision to consolidate its AI offerings under the relaunched Qwen app, which debuted on November 18, just a day prior to LingGuang’s launch. He Zhengyu, CTO of Ant Group, indicated that the timing of the two releases was coincidental and not pre-coordinated.
Historically, Alibaba has not prioritized consumer AI applications. However, in 2025, the company began to ramp up its consumer strategy, with plans to compete directly in the consumer AI sector. During the launch of Qwen, Alibaba emphasized its intent to establish a presence in this space as a new entry point for users. To achieve this, the company is diversifying its approach rather than relying on a single product strategy. “Jack Ma encouraged us to push ourselves to the top of the app store rankings,” said He.
Given the rapid progress in AI capabilities and an increasingly competitive landscape, this multi-faceted strategy is seen internally as a prudent approach. He illustrated this strategy with an analogy: “If you’re trying to find water in a desert, you wouldn’t send everyone in one direction. You’d send teams in several directions.”
From a product standpoint, the Qwen app leverages Alibaba’s underlying model capabilities, excelling in general Q&A, long-form writing, and complex reasoning tasks. In contrast, LingGuang emphasizes mobile-native interactions, aiming to deliver rich, multimodal content while also supporting code generation for mini apps.
LingGuang is not designed as a universal assistant, nor does it seek to compete with companionship-oriented platforms such as Doubao. Instead, it is positioned as an efficiency tool. Its most significant distinction is in how it presents information, moving beyond conventional chat interfaces. It can produce images, animations, and 3D models, enhancing user comprehension. Cai Wei, LingGuang’s product lead, compared this shift to a teacher who illustrates concepts visually to aid understanding.
For instance, when prompted for a recipe for sweet-and-sour ribs, traditional AI might return a lengthy, text-heavy response, while LingGuang generated a visual card within seconds, complete with an image of the dish, step-by-step instructions, and a visually accessible layout designed for quick scanning. “We want AI-generated answers to achieve that level of information density,” Cai stated.
This design approach not only aligns with natural human information processing but also adapts across various scenarios, allowing users to receive immediate, comprehensible presentations of data, whether it be a chart while drafting a paper or a 3D model during home renovation discussions.
LingGuang’s second major feature is its ability to generate interactive mini apps tailored to user requests. If a user asks for a timer, for example, LingGuang can create one instantly. While the concept of generating apps from simple instructions is not novel, the challenge lies in ensuring these AI-generated outputs are functional and scalable.
The complexity of this task is rooted in model architecture and engineering. A brief instruction in Mandarin, such as “create a centered blue button,” may necessitate significant underlying code to generate a usable component. LingGuang employs engineering optimizations to mitigate computation load and maintain performance, focusing on coding capabilities as a core strength.
Ant Group’s decision to develop a dedicated AGI team named Inclusion AI demonstrates its commitment to advancing artificial general intelligence. This strategic choice allows Ant to pursue narrow yet impactful directions, focusing on coding capabilities and multimodal outputs while not competing directly with general-purpose assistants like Doubao.
As LingGuang positions itself as an efficiency tool, it aims to simplify user interactions and enhance productivity. The long-term vision includes creating a mini app ecosystem with a marketplace and sharing tools, allowing users to easily create and consume mini apps. “We want to lower the barriers for anyone to create and consume mini apps,” Cai affirmed, underscoring LingGuang’s potential to reshape user engagement in the AI landscape.
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