Zuckerberg’s New AI Model Costs 75% Less Than Rivals — Here’s His Pitch

Photo of Danielle Liverance
By Danielle Liverance Published

Quick Read

  • Meta launched Muse Spark 1.1 at 75% below rival pricing, marking its first proprietary API business after years of championing open-source AI.

  • Broadcom's Q2 AI revenue jumped 143% to $10.8 billion, with Meta co-developing the custom Iris chip via TSMC to drive down inference costs.

  • Zuckerberg admitted AI growth lags internal expectations, and with frontier model Watermelon still unfinished, $145 billion in capex hinges on Muse Spark's pricing edge.

  • This lithium producer surpassed a $1B private valuation, joining some of America's most powerful startups. Now you can invest in EnergyX alongside global giants like General Motors, but only through July 16. (sponsor)

This post may contain links from our sponsors and affiliates, and Flywheel Publishing may receive compensation for actions taken through them.
Zuckerberg’s New AI Model Costs 75% Less Than Rivals — Here’s His Pitch

© Justin Sullivan / Getty Images

Meta (NASDAQ:META | META Price Prediction) is charging businesses to use one of its AI models for the first time, undercutting rivals significantly. On July 9, 2026, Meta launched Muse Spark 1.1, a frontier model’s paid developer tier costs roughly 25% of what OpenAI and Anthropic charge, meaning developers pay about 75% less. Mark Zuckerberg’s pitch: make AI cheap enough that everyone builds on Meta’s platform.

META price target

This marks a genuine pivot. Meta championed open-source AI; Muse Spark 1.1 is proprietary and revenue-focused. As Zuckerberg told Bloomberg on July 9, “Since this isn’t an open-source model, this is really the first time we’re seriously launching an API business.”

The Pitch in Zuckerberg’s Words

Where rivals charge $5 to $10 per million input tokens and $30 to $50 per million output tokens, Meta costs roughly a quarter of that. Vals.ai found Muse Spark 1.1 runs at about one-tenth the cost of GPT-5.5, while AnalysisAI measured input costs roughly 75% below Anthropic’s Claude Opus 4.8 and output costs about 83% lower. “The pricing is going to be very aggressive and attractive,” Zuckerberg framed it as a mission: “Someone has to build these models and make sure the highest quality intelligence is available to everyone.”

Why Meta Had to Do This

Meta committed $125 to $145 billion in 2026 capex, its largest ever, with shares gaining 14.81% in the week ending July 10. In April, Zuckerberg said: “We had a milestone quarter with strong momentum across our apps and the release of our first model from Meta Superintelligence Labs.” Meta is co-developing a custom “Iris” AI chip with Broadcom, manufactured by TSMC, cutting Nvidia dependence and lowering inference costs. A leaked memo revealed plans to put Iris into production in September and double computing capacity to 14 gigawatts. Our AI infrastructure research covers second-order beneficiaries in this report on power and data-center names beyond chipmakers.

Ticker Exposure to Meta’s AI Buildout

Broadcom (NASDAQ:AVGO) is tied to Iris and posted Q2 FY2026 AI semiconductor revenue of $10.8 billion, up 143% year over year. CEO Hock Tan said: “The momentum continues and in Q3 we expect semiconductor revenue from AI to grow over 200 percent year-over-year to $16.0 billion.” Taiwan Semiconductor (NYSE:TSM) fabricates both Iris and Nvidia GPUs. Its May 2026 revenue rose 30.1% year over year. SemiAnalysis projects Meta’s total AI compute will surpass OpenAI’s and Anthropic’s by year end.

The Open Question

On July 2, he admitted AI “hasn’t really accelerated in the way we expected” internally, creating tension with this week’s bullish launch. Muse Spark 1.1 competes on price and capability while still trailing GPT-5.5 on outright performance. Meta’s true frontier model, “Watermelon,” is still in development. If it delivers, the bet gets interesting. If not, Meta may have started a price war it cannot win. Can 75%-cheaper AI earn back a $145 billion infrastructure bill?

Contact [email protected] for any questions or corrections.

Photo of Danielle Liverance
About the Author Danielle Liverance →

I've spent more than 15 years inside enterprise software, working alongside the finance, sales operations, and HR leaders who run the revenue engines at some of the largest tech companies in the country.

My day job is helping enterprise executives make smarter decisions about retention, compensation, and growth. These are the same operational levers that show up in every earnings report investors actually read. That perspective shapes my writing for 24/7 Wall St.

The headline numbers are easy. The interesting stuff is underneath: how companies make money, what executives are worried about, and what any of it means for the person checking their 401(k) on a Sunday afternoon. I write about personal finance and business as someone who has spent her career inside the rooms where these decisions get made.

Featured Reads

Our top personal finance-related articles today. Your wallet will thank you later.

Continue Reading

Top Gaining Stocks

FDS Vol: 909,036
IT Vol: 1,372,160
INTU Vol: 5,664,108
VLO Vol: 2,780,306
PAYC Vol: 620,555

Top Losing Stocks

CTRA Vol: 73,319,495
ORCL Vol: 56,067,130
INTC Vol: 99,324,215
LRCX Vol: 9,754,734
ON Vol: 9,442,449