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Lenovo’s Latest Wacky Concepts Include a Laptop With a Built-In Portable Monitor

Lenovo’s Latest Wacky Concepts Include a Laptop With a Built-In Portable Monitor

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Do you like having a second screen with your computer setup? What if your laptop could carry a second screen for you? That’s the idea behind Lenovo’s latest proof of concept, the ThinkBook Modular AI PC, announced at Mobile World Congress in Barcelona.

Lenovo is never shy to show off wacky, weird concept laptops. We’ve seen a PC with a transparent screen, one with a rollable OLED screen, a swiveling screen, and another with a flippy screen. At CES earlier this year, the company showed off a gaming laptop with a display that expands at the push of a button. Sometimes, these concepts turn into real products that go on sale (often in limited quantities).

At MWC 2026, Lenovo trotted out three concepts. While it’s unclear whether any of them will become real, purchasable products, there’s some unique utility here, and a peek at how computing experiences could change in the future.

A Laptop With a Built-In Portable Screen

The ThinkBook Modular AI PC has a second screen hanging magnetically off the back of the laptop, and it can show content to people sitting in front of you.

Photograph: Julian Chokkattu

Image may contain Computer Electronics Laptop Pc Computer Hardware Computer Keyboard Hardware Monitor and Screen

This is with the second screen removed from the back and placed in front of the main display. The keyboard is removable and works via Bluetooth.

Photograph: Julian Chokkattu

As someone with a multi-screen setup at home and a fondness for portable monitors, the ThinkBook Modular AI PC appeals to me the most. At first glance, it looks like a normal laptop. Take a look behind, and you’ll notice there’s a second screen magnetically hanging off the back of the laptop, like a koala carrying a baby on its back.

The screen is connected to the laptop using pogo-pin connectors, so you can use it in this state to display content to people in front of you, say, if you were making a presentation during a meeting. Alternatively, you can pop this second screen off, remove a hidden kickstand resting under the laptop, and magnetically attach it to the 14-inch screen so that you have a traditional portable monitor experience. (You’ll need to connect this to the laptop via a USB-C cable in this orientation.)

If you don’t have the desk space for that orientation, you can always remove the keyboard from the base and pop the second screen there—it’ll auto-connect to the laptop via the pogo pins, and you’ll be able to use the Bluetooth keyboard to type on a dual-screen setup that resembles the Asus ZenBook Duo. The whole system is a fantastically portable method of improving productivity on the go, and the laptop isn’t too thick or cumbersome.

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White House officials are exploring official government oversight of new AI models, according to the New York Times.

U.S. officials, speaking on the condition of anonymity, told the publication that the Trump administration is forming an AI working group composed of tech leaders and government representatives. The group will be tasked with outlining potential oversight procedures for new models launching to market, including formal review processes, the Times reported.

SEE ALSO: Student sues matchmaking app for allegedly stealing her likeness for an ad

The proposed plans were discussed at a White House meeting last week with representatives from Anthropic, Google, and OpenAI.

Potentially influenced by regulatory processes announced by UK regulators, which relegate AI oversight to relevant government bodies, the working group would also determine which U.S. agencies would be tasked with oversight. Some officials have suggested the National Security Agency (NSA), the White House Office of the National Cyber Director, and the director of national intelligence take the lead, while others have even suggested revitalizing the Biden-era Center for A.I. Standards and Innovation, according to the Times.

The administration has reversed its stance on AI regulation in recent months, despite announcing a federal AI action plan that pulled back on regulation of tech companies and threatened to reduce federal funding for states that impeded AI infrastructure efforts through regulation. Trump’s One Big Beautiful Bill also included limits on state governments’ AI regulation, originally proposing a 10-year moratorium on state action in favor of federal oversight.

Trump appointee and FCC chairman Brendan Carr has also advocated for a light-touch approach to AI regulation.

#Trump #federal #model #oversight">Trump considering federal AI model oversight White House officials are exploring official government oversight of new AI models, according to the New York Times. U.S. officials, speaking on the condition of anonymity, told the publication that the Trump administration is forming an AI working group composed of tech leaders and government representatives. The group will be tasked with outlining potential oversight procedures for new models launching to market, including formal review processes, the Times reported. SEE ALSO: Student sues matchmaking app for allegedly stealing her likeness for an ad The proposed plans were discussed at a White House meeting last week with representatives from Anthropic, Google, and OpenAI. Mashable Light Speed Potentially influenced by regulatory processes announced by UK regulators, which relegate AI oversight to relevant government bodies, the working group would also determine which U.S. agencies would be tasked with oversight. Some officials have suggested the National Security Agency (NSA), the White House Office of the National Cyber Director, and the director of national intelligence take the lead, while others have even suggested revitalizing the Biden-era Center for A.I. Standards and Innovation, according to the Times. The administration has reversed its stance on AI regulation in recent months, despite announcing a federal AI action plan that pulled back on regulation of tech companies and threatened to reduce federal funding for states that impeded AI infrastructure efforts through regulation. Trump’s One Big Beautiful Bill also included limits on state governments’ AI regulation, originally proposing a 10-year moratorium on state action in favor of federal oversight. Trump appointee and FCC chairman Brendan Carr has also advocated for a light-touch approach to AI regulation. #Trump #federal #model #oversight

government oversight of new AI models, according to the New York Times.

U.S. officials, speaking on the condition of anonymity, told the publication that the Trump administration is forming an AI working group composed of tech leaders and government representatives. The group will be tasked with outlining potential oversight procedures for new models launching to market, including formal review processes, the Times reported.

SEE ALSO: Student sues matchmaking app for allegedly stealing her likeness for an ad

The proposed plans were discussed at a White House meeting last week with representatives from Anthropic, Google, and OpenAI.

Potentially influenced by regulatory processes announced by UK regulators, which relegate AI oversight to relevant government bodies, the working group would also determine which U.S. agencies would be tasked with oversight. Some officials have suggested the National Security Agency (NSA), the White House Office of the National Cyber Director, and the director of national intelligence take the lead, while others have even suggested revitalizing the Biden-era Center for A.I. Standards and Innovation, according to the Times.

The administration has reversed its stance on AI regulation in recent months, despite announcing a federal AI action plan that pulled back on regulation of tech companies and threatened to reduce federal funding for states that impeded AI infrastructure efforts through regulation. Trump’s One Big Beautiful Bill also included limits on state governments’ AI regulation, originally proposing a 10-year moratorium on state action in favor of federal oversight.

Trump appointee and FCC chairman Brendan Carr has also advocated for a light-touch approach to AI regulation.

#Trump #federal #model #oversight">Trump considering federal AI model oversight

White House officials are exploring official government oversight of new AI models, according to the New York Times.

U.S. officials, speaking on the condition of anonymity, told the publication that the Trump administration is forming an AI working group composed of tech leaders and government representatives. The group will be tasked with outlining potential oversight procedures for new models launching to market, including formal review processes, the Times reported.

SEE ALSO: Student sues matchmaking app for allegedly stealing her likeness for an ad

The proposed plans were discussed at a White House meeting last week with representatives from Anthropic, Google, and OpenAI.

Potentially influenced by regulatory processes announced by UK regulators, which relegate AI oversight to relevant government bodies, the working group would also determine which U.S. agencies would be tasked with oversight. Some officials have suggested the National Security Agency (NSA), the White House Office of the National Cyber Director, and the director of national intelligence take the lead, while others have even suggested revitalizing the Biden-era Center for A.I. Standards and Innovation, according to the Times.

The administration has reversed its stance on AI regulation in recent months, despite announcing a federal AI action plan that pulled back on regulation of tech companies and threatened to reduce federal funding for states that impeded AI infrastructure efforts through regulation. Trump’s One Big Beautiful Bill also included limits on state governments’ AI regulation, originally proposing a 10-year moratorium on state action in favor of federal oversight.

Trump appointee and FCC chairman Brendan Carr has also advocated for a light-touch approach to AI regulation.

#Trump #federal #model #oversight

On May 4, 2026, the U.S. Securities and Exchange Commission filed an amended complaint to add the Elon Musk Revocable Trust dated July 22, 2003 (the “Revocable Trust”) as a defendant to this action. The amended complaint alleges that the defendants failed to timely file a beneficial ownership report with the Commission after the Revocable Trust acquired beneficial ownership of more than five percent of the outstanding shares of Twitter, Inc. common stock, in violation of the beneficial ownership reporting requirements under the Securities Exchange Act of 1934 (“Exchange Act”).

The SEC simultaneously moved for entry of a consent final judgment as to the Revocable Trust. Without admitting or denying the allegations of the complaint as to the Revocable Trust, the Revocable Trust consented to entry of a final judgment, subject to court approval, that would permanently enjoin it from violating Section 13(d) of the Exchange Act and Rule 13d-1 thereunder and order it to pay a civil penalty of $1.5 million.

As explained in the consent motion, if the court enters the proposed final judgment as to the Revocable Trust as proposed by the Revocable Trust and the SEC, the SEC will file a stipulated dismissal of Elon Musk in his personal capacity, which will resolve this case in its entirety.

#Elon #Musk #settle #feds #Twitter #lawsuit #pocket #changeElon Musk,Law,News,Policy,Tech,Twitter – X">Elon Musk will settle the feds’ Twitter lawsuit with pocket changeOn May 4, 2026, the U.S. Securities and Exchange Commission filed an amended complaint to add the Elon Musk Revocable Trust dated July 22, 2003 (the “Revocable Trust”) as a defendant to this action. The amended complaint alleges that the defendants failed to timely file a beneficial ownership report with the Commission after the Revocable Trust acquired beneficial ownership of more than five percent of the outstanding shares of Twitter, Inc. common stock, in violation of the beneficial ownership reporting requirements under the Securities Exchange Act of 1934 (“Exchange Act”).The SEC simultaneously moved for entry of a consent final judgment as to the Revocable Trust. Without admitting or denying the allegations of the complaint as to the Revocable Trust, the Revocable Trust consented to entry of a final judgment, subject to court approval, that would permanently enjoin it from violating Section 13(d) of the Exchange Act and Rule 13d-1 thereunder and order it to pay a civil penalty of .5 million.As explained in the consent motion, if the court enters the proposed final judgment as to the Revocable Trust as proposed by the Revocable Trust and the SEC, the SEC will file a stipulated dismissal of Elon Musk in his personal capacity, which will resolve this case in its entirety.#Elon #Musk #settle #feds #Twitter #lawsuit #pocket #changeElon Musk,Law,News,Policy,Tech,Twitter – X


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.

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.

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.

Image AI models now drive app growth, beating chatbot upgrades | TechCrunch 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. 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. 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. Image Credits:Appfigures 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. 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.) Image Credits:Appfigures Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue. Techcrunch event San Francisco, CA | October 13-15, 2026 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 1,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release. Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue. Among the three, only ChatGPT turned the increased attention into actual dollars. OpenAI’s 4o image-generation model led to an estimated million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said. Image Credits:Appfigures 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. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai
Image Credits:Appfigures

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.

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.)

Image Credits:Appfigures

Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue.

Techcrunch event

San Francisco, CA | October 13-15, 2026

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’s 4o image model release.

Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue.

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.

Image Credits:Appfigures

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.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai">Image AI models now drive app growth, beating chatbot upgrades | TechCrunch 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. 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. 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. Image Credits:Appfigures 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. 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.) Image Credits:Appfigures Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue. Techcrunch event San Francisco, CA | October 13-15, 2026 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 1,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release. Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue. Among the three, only ChatGPT turned the increased attention into actual dollars. OpenAI’s 4o image-generation model led to an estimated million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said. Image Credits:Appfigures 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. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai

new models powering the conversational experiences drove more demand, alongside the new features like a voice chat interface.

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.

Image AI models now drive app growth, beating chatbot upgrades | TechCrunch 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. 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. 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. Image Credits:Appfigures 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. 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.) Image Credits:Appfigures Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue. Techcrunch event San Francisco, CA | October 13-15, 2026 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 1,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release. Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue. Among the three, only ChatGPT turned the increased attention into actual dollars. OpenAI’s 4o image-generation model led to an estimated million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said. Image Credits:Appfigures 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. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai
Image Credits:Appfigures

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.

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.)

Image Credits:Appfigures

Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue.

Techcrunch event

San Francisco, CA | October 13-15, 2026

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’s 4o image model release.

Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue.

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.

Image Credits:Appfigures

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.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai">Image AI models now drive app growth, beating chatbot upgrades | TechCrunch


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.

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.

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.

Image AI models now drive app growth, beating chatbot upgrades | TechCrunch 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. 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. 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. Image Credits:Appfigures 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. 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.) Image Credits:Appfigures Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue. Techcrunch event San Francisco, CA | October 13-15, 2026 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 1,000 in estimated gross consumer spending during the 28-day window following its release, even though it produced a larger spike in downloads than ChatGPT’s 4o image model release. Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue. Among the three, only ChatGPT turned the increased attention into actual dollars. OpenAI’s 4o image-generation model led to an estimated million in gross consumer spending over the 28 days after its launch, compared with its prior baseline, Appfigures said. Image Credits:Appfigures 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. When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai
Image Credits:Appfigures

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.

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.)

Image Credits:Appfigures

Still, the report cautioned, additional downloads don’t always translate into increased mobile revenue.

Techcrunch event

San Francisco, CA | October 13-15, 2026

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’s 4o image model release.

Meta AI’s launch of Vibes also led to additional downloads, but no meaningful revenue.

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.

Image Credits:Appfigures

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.

When you purchase through links in our articles, we may earn a small commission. This doesn’t affect our editorial independence.

#Image #models #drive #app #growth #beating #chatbot #upgrades #TechCrunchai apps,ChatGPT,gemini,image models,meta ai

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