Image AI models now drive app growth, beating chatbot upgrades

图像 AI 模型现已成为应用增长的驱动力，表现优于聊天机器人升级

Image model releases are driving growth for AI mobile apps, generating 6.5x more downloads than traditional model updates, according to a new report from app intelligence provider Appfigures. 根据应用情报提供商 Appfigures 的一份最新报告，图像模型的发布正在推动 AI 移动应用的增长，其下载量是传统模型更新的 6.5 倍。

This marks a shift from earlier days, when the release of new models powering the conversational experiences drove more demand, alongside the new features like a voice chat interface. 这标志着一种转变：在早期，推动对话体验的新模型发布，以及语音聊天界面等新功能，往往能带来更大的需求。

For instance, ChatGPT and Gemini each added tens of millions of new downloads after releasing their respective image models, Appfigures found. For Google’s Gemini, the release of its image model Nano Banana drove an additional 22+ million downloads in the 28 days following the introduction of the Gemini 2.5 Flash image model last August. This launch lifted the app’s downloads by more than 4x over that period, the data showed. Appfigures 发现，例如 ChatGPT 和 Gemini 在发布各自的图像模型后，下载量均增加了数千万次。对于谷歌的 Gemini 而言，去年 8 月推出 Gemini 2.5 Flash 图像模型后的 28 天内，其 Nano Banana 图像模型的发布带来了超过 2200 万次的额外下载量。数据显示，此次发布使该应用在同期内的下载量增长了 4 倍以上。

Meanwhile, ChatGPT added more than 12 million incremental installs in the 28 days after the introduction of its GPT-4o image model in March of last year. That’s roughly 4.5x more downloads than it saw for its GPT-4o, GPT-4.5, and GPT-5 model releases, Appfigures pointed out. 与此同时，ChatGPT 在去年 3 月推出 GPT-4o 图像模型后的 28 天内，新增了超过 1200 万次安装。Appfigures 指出，这大约是其 GPT-4o、GPT-4.5 和 GPT-5 模型发布时下载量的 4.5 倍。

Other model releases followed similar trends, though on a smaller scale. Meta AI’s introduction of its AI video feed Vibes added an estimated 2.6 million incremental downloads in the 28 days after its September 2025 release. (Yes, technically, this is a video model, but it’s ultimately about visual content, not just text.) 其他模型的发布也呈现出类似的趋势，尽管规模较小。Meta AI 在 2025 年 9 月发布其 AI 视频流 Vibes 后的 28 天内，估计增加了 260 万次额外下载。（是的，从技术上讲，这是一个视频模型，但它最终属于视觉内容，而不仅仅是文本。）

Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue. 不过，该报告提醒称，下载量的增加并不总是能转化为移动端收入的增长。

Instead, new image model releases give people a reason to install the app and try out its improved image-generation capabilities. That doesn’t mean they’ll necessarily convert to paying subscribers. For example, Appfigures noted that Nano Banana drove only $181,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’4o image model release. Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue. 相反，新图像模型的发布只是给了人们安装应用并尝试其改进后的图像生成功能的理由。这并不意味着他们一定会转化为付费订阅用户。例如，Appfigures 指出，Nano Banana 在发布后的 28 天窗口期内，估计仅带来了 18.1 万美元的消费者总支出，尽管其下载量激增幅度超过了 ChatGPT 的 4o 图像模型发布。Meta AI 的 Vibes 发布也带来了额外的下载量，但没有产生显著的收入。

Among the three, only ChatGPT turned the increased attention into actual dollars. OpenAI’s 4o image-generation model led to an estimated $70 million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said. 在这三者中，只有 ChatGPT 将增加的关注度转化为了实际收益。Appfigures 表示，与之前的基准相比，OpenAI 的 4o 图像生成模型在发布后的 28 天内带来了约 7000 万美元的消费者总支出。

The company also looked at DeepSeek in its analysis, but it didn’t fit the pattern. While DeepSeek R1 drove 28 million downloads after its January 2025 release, it wasn’t a typical model comparison event. This was DeepSeek’s breakout moment, when it went from being relatively unknown to an overnight sensation as the tech industry learned about the techniques it used to train its AI models at a fraction of the cost of its competitors. This case highlights how curiosity can drive downloads — though in this instance, the interest wasn’t tied to an image model. 该公司在分析中也考察了 DeepSeek，但它并不符合这一模式。虽然 DeepSeek R1 在 2025 年 1 月发布后带来了 2800 万次下载，但这并非典型的模型对比事件。这是 DeepSeek 的爆发时刻，随着科技行业了解到其以竞争对手极低成本训练 AI 模型的技术，它从相对默默无闻一跃成为一夜成名的现象级产品。这一案例凸显了好奇心如何驱动下载量——尽管在这种情况下，这种兴趣并非源于图像模型。