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The Next Generation of Modular, Repairable Laptops May Have More Than One Screen

The Next Generation of Modular, Repairable Laptops May Have More Than One Screen

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The latest ThinkBook X1 Carbon, which Lenovo debuted with extra fanfare back at CES 2026, boasts extra repairability beyond any other laptop in the company’s ultraportable repertoire. However, that easily removable keyboard and chassis were built more for the sake of trained technicians rather than the lowly laptop user who just wants to swap out their USB-C port for HDMI. Lenovo’s latest ThinkPad concept goes a step further. It promises a whole new level of modularity that is even more ambitious than Framework’s current design. It’s only held back by Lenovo’s need to hang on to too many proprietary components.

This Modular AI Concept feels like an adaptation of so many competitors, such as Framework and Asus. With the keyboard on, it resembles a regular 14-inch ThinkBook laptop. The keyboard then comes off, revealing a platform where you can stick in a secondary screen. It should remind you of the Asus Zenbook Duo with similar dual-screen functionality. The modularity doesn’t stop there. That screen can also attach to the rear of the laptop lid. In this mode, users can mirror their screen to show somebody on the outside what they’re working on.

© Adriano Contreras / Gizmodo

That secondary screen can also hang out as an external display thanks to an integrated kickstand. It’s not Bluetooth enabled, meaning you’ll need to plug it into one of the ThinkBook’s available USB-C ports. Taking a page from Framework, two of the laptop’s four ports are removable and swappable with—ostensibly—some other variety of port. If you know you’ll be working with photos, you could exchange it for an SD card slot.

It just needs an extra touch of Framework

I was starting to feel the excitement building. Finally, Lenovo was going full Framework and promising its business-class laptops could have the customizability we’ve longed for for so long. Then reality set in. Unlike the Framework 13, the ThinkBook concept uses a pin connection for its removable ports. Framework, on the other hand, relies on a USB-C system that enables more users to install any number of port connections. That means the ThinkBook is far less customizable for the DIYers who enjoy creating their own modules for their laptops.

There’s a lot to like about the ThinkPad concept, except perhaps for the durability. The pin section behind the monitor became unglued as I removed it from the laptop. Lenovo fished me out a replacement so I could finish testing it. Still, I’ll admit the idea behind this laptop is especially enticing. The Zenbook Duo proved we can have a high-powered dual-screen laptop with strong battery life. Having one with even more modularity could make the ThinkPad design more worthwhile beyond the standard business laptop user. Lenovo just needs to eschew the module’s pin connection and stick a big red TrackPoint “nipple” in the center of the keyboard, and the ThinkPad Modular could be the one ultraportable laptop to rule them all.

As with any proof of concept, you shouldn’t expect a finalized product. It’s Lenovo’s focus on proprietary ports that dampens my enthusiasm. We should all enjoy a more modular, repairable design. We’d be better off if Lenovo could trust its users to do it themselves.

If you don’t care about modularity, how about a 3D screen?

Lenovo Yoga Book Pro 3d Concept 7
That top screen uses eye tracking to show users a faux-3D image, while the bottom touchscreen will display the models in 2D. © Adriano Contreras / Gizmodo

As if Lenovo didn’t already have enough concept devices in tow, it was also adamant I check out its Yoga Book Pro 3D concept. This device is exactly what it sounds like: a massive, dual-screen laptop, with one screen built for glasses-less 3D. Sure, it’s running on an Intel Core Ultra 7 processor (Lunar Lake, not Panther Lake, unfortunately) and an Nvidia GeForce RTX 5070 mobile GPU, but what you really care about are those twin screens.

Lenovo has shown me previous monitor concepts and prototypes, like its ThinkVision 2D/3D monitor and a similar laptop with a 3D screen. Those devices make use of an attached webcam to track users’ eyes. Then, the screen shows a different image to each eye, creating a stereoscopic effect that results in users perceiving a 3D image. Samsung has this technology in its Odyssey 3D gaming monitor and upcoming 6K-resolution 3D redux. The Yoga Book Pro 3D Concept is built more for creators than gamers. It includes a touchscreen on the bottom that works with a stylus. Users can manipulate a 3D model in a graphics app, then see how it looks in 3D on the top screen.

If 3D screens take off—despite my enthusiasm for them, that’s a big ‘if’—then these types of devices may become necessary for creators and 3D modelers. The bottom screen also makes use of “pads” that react to the display, enabling a color picker or a lighting adjuster. Believe it or not, it’s that small feature that’s the least useful of this incredibly odd laptop.

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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.

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