Meta Apps - Facebook, WhatsApp, Instagram, and Threads

Meta platforms Facebook, WhatsApp, Instagram, and Threads on an Apple iPhone (Getty Images)

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Meta is testing out premium subscriptions on Instagram, Facebook, and WhatsApp

Ahead of its earnings, expected after the bell today, Meta has announced plans to trial a paid tier on its apps.

1/28/26 7:37AM

The list of periodic charges granting entry to much of the essential watching, listening, and even tasting that modern life demands might now be getting one subscription service longer.

On Monday, Meta told TechCrunch that it plans to trial new premium subscriptions on social media apps Instagram, Facebook, and WhatsApp in the coming months. According to the company, the paid offerings will give users access to exclusive features such as expanded AI capabilities, though the “core experiences” will (supposedly) remain the same for users in the ad-supported tier.

Deals on Reels

Still, unlike Spotify and Netflix, which actually pay for the content on their platforms and are only incrementally looking to advertising to juice up their bottom lines, Meta is already squeezing plenty of revenue from users without a paid subscriber model. In its third-quarter results back in October, the company reported total revenues of $51.2 billion — about $50 billion (~98%) of which came directly from advertising.

Meta’s ability to turn eyeballs into cash has seen it rake in a cumulative $813 billion from ads since 2019. And, having put ads in WhatsApp for the first time last June, this figure is only expected to get larger when the tech behemoth reports its quarterly earnings later today. Indeed, Meta’s only division in which consumers pay up rather than advertisers — Reality Labs — is also the only one that continues to light billions of dollars on fire.

Face value

The new tiered model comes as Meta looks to expand its AI offering, with the tech giant outlining plans to scale Manus — the web-browsing, content-producing AI agent it acquired right at the end of 2025 — and short-form video generator Vibes as part of the subscription plans.

But what might convince some more social media-savvy users to start paying up are additional features designed to give “more control” over Instagram accounts in particular, including creating unlimited audience lists, seeing which followers don’t follow them back, and viewing a Story without the poster seeing that they viewed it.

Jon Keegan1h

FT: Meta considering “tens of billions” in new capital to fund AI

Just days after Google announced a monster $85 billion upsized equity raise, the extremely profitable Meta is seeking to sell “tens of billions of dollars” in stock, according to a new report from the FT.

Meta is planning on spending between $125 billion to $145 billion on AI capex this year alone.

Shares dropped more than 5% on the news.

Meta weighs big equity raising after blockbuster Google deal

Rani Molla

Meta is supercharging its subscription businesses

The free-app giant never really cared about recurring revenue. Now, it’s launching paid plans for all sorts of stuff.

Jon Keegan7h

FT: Anthropic staff helping the NSA use Mythos for offensive cyberattacks

Anthropic’s Mythos AI model was deemed too dangerous to release to the public, with the company citing its ability to orchestrate novel cyberattacks.

And that’s just what the National Security Agency is doing, with the help of Anthropic staff embedded at the agency, according to a report from the Financial Times.

Only a small number of companies and US allies have been given access to the advanced model, which means America’s adversaries have not had the chance to shore up their defenses against the AI model’s new offensive capabilities.

The arrangement is especially unusual as the Pentagon has deemed Anthropic’s AI a national security supply chain risk — effectively blacklisting it for defense work — in response to the company’s refusal to allow its technology to be used for any legal application, which could include autonomous killing or mass surveillance. Anthropic is currently suing the US government to fight the determination.

US National Security Agency using Anthropic’s Mythos for cyber attacks

Rani Molla8h

Longtime Tesla bear JPMorgan upgraded Tesla and raised its price target to $475 from $145

For more than a decade, JPMorgan was Wall Street’s most stubborn Tesla skeptic, anchored by auto analyst Ryan Brinkman’s strict focus on traditional car fundamentals and near-term delivery numbers.

But JPM recently handed coverage of the stock to a new analyst, Rajat Gupta, who is throwing that playbook out the window. In a note Friday, the firm upgraded Tesla to “neutral” from “underweight” and raised its price target 228% to $475 from $145. (The analyst consensus on FactSet is $403.) Instead of focusing on the company’s struggling vehicle business, the new analyst is orienting himself more toward Tesla’s idea of the future, now modeling Tesla’s physical AI and robotaxi fleets all the way out to the year 2040.

Here are the main reasons for the capitulation:

Looking past the car lot: Gupta argues that Tesla “is at the forefront of physical AI, entering uncharted TAMs” and therefore “deserves the benefit of the doubt to be valued on LT earnings potential” rather than near-term speed bumps.
Unmatched vertical integration: Tesla’s control over everything from battery cells to custom silicon gives it a massive moat. JPM notes this starting point advantage is “unmatched at an industrial level scale” and “still somewhat under-appreciated and misunderstood.”
The AWS flywheel effect: Deploying Optimus robots inside its own factories “should not only lower COGS for the base automotive business, but more importantly, help validate the product at an industrial scale.” Gupta called it “a classic flywheel effect, somewhat analogous to AWS and Kiva at AMZN.”

For Tesla bulls who have argued for years that this is an AI company and not a carmaker, JPM’s sudden $3.9 trillion valuation model is the ultimate validation.

Anthropic ponders self-improving AI

Anthropic says Claude already writes 80% of its code. A new post asks what happens when the models can improve themselves — and whether anyone could stop them.

Jon Keegan8h