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QCOM Stock Jumps As Qualcomm Rewires Future Around AI Data Centers Thumbnail

QCOM Stock Jumps As Qualcomm Rewires Future Around AI Data Centers

BRYCE TUOHEYUPDATED JUN. 25, 2026, 9:19 AM ET
Reviewed by Tim Sykesand Fact-checked by Matt Monaco

QUALCOMM Incorporated stocks have been trading up by 7.86 percent amid strong AI chip momentum and robust earnings outlook.

Key Takeaways For QCOM Traders

  • Qualcomm doubled its 2029 non-handset revenue target to $40B and now guides to more than $18 in non-GAAP EPS, with handsets shrinking to roughly one-third of QCT revenue.
  • The company launched its Dragonfly AI data center portfolio, centered on the C1000 CPU and AI300 accelerators, targeting power-efficient, full-stack AI infrastructure.
  • Meta signed a multi-generation deal to use Qualcomm’s Dragonfly C1000 CPUs in its next-gen data center fleet starting in 2H 2028, adding long-term revenue visibility.
  • Qualcomm agreed to buy AI software firm Modular to build an open, hardware-agnostic AI stack spanning CPUs, GPUs, NPUs and ASICs from edge to cloud.
  • After these announcements and new growth targets, QCOM shares spiked roughly 9–11% to around $215.50 as traders embraced the diversification and data center AI strategy.

Candlestick Chart

Live Update At 09:18:45 EDT: On Thursday, June 25, 2026 QUALCOMM Incorporated stock [NASDAQ: QCOM] is trending up by 7.86%! Discover the key drivers behind this movement as well as our expert analysis in the detailed breakdown below.

Quick Financial Overview

QCOM is trading like a stock that just got a new playbook. Over the last couple of weeks, Qualcomm shares have swung between about $191 and $255, with recent closes clustering in the low-$200s. The stock pulled back from the $250 area to sub-$200, then bounced toward $215–$225 as traders priced in the new AI story.

Daily candles show heavy volatility but a clear support zone building around $200. Each dip into the high-$190s and low-$200s has attracted buyers, suggesting dip-buying behavior from active QCOM traders. That matters, because it often signals confidence in the new narrative rather than panic selling.

Intraday, the 5-minute chart around the latest move shows tight consolidation between roughly $216 and $222 before and after the headlines, a classic base-building pattern after a sharp rally. QCOM is not trading like a broken chart; it’s trading like a stock pausing after a re-rating.

More Breaking News

Fundamentally, Qualcomm is backing that chart action with strong metrics. Revenue sits near $44.3B with a gross margin around 54.8% and an EBIT margin close to 28%. Returns on equity above 36% and a current ratio of 2.4 show both high profitability and solid balance-sheet strength. For traders, that combination—volatile price action on top of durable fundamentals—is exactly the kind of backdrop that can fuel repeat momentum setups.

Why Traders Are Locked In On QCOM Now

Qualcomm used its latest Investor Day on 2026/06/24 to tell traders one thing: this is no longer just a handset chip story. QCOM sharply raised its 2029 non-handset revenue target to $40B, roughly double prior guidance. It wants more than $15B of that from data center AI alone and another $10B from automotive, backed by a $65B design-win pipeline. On top of that, the company is guiding to non-GAAP EPS above $18 in fiscal 2029 and expects handsets to drop to about one-third of QCT revenue.

That shift is huge. For years, traders treated QCOM as a smartphone proxy. Now Qualcomm is pitching itself as a diversified AI and automotive platform, with data centers in the middle of the story.

The most eye-catching piece is the new Dragonfly data center portfolio. Qualcomm introduced the Dragonfly C1000 CPU and AI300 inference accelerators using a new High Bandwidth Compute memory technology, plus connectivity solutions. It is targeting agentic AI workloads—complex, always-on AI “agents” that need high performance without blowing out power or cost budgets. QCOM is trying to carve a lane as the low-power, cost-efficient full-stack provider.

Crucially, this is not just slideware. Meta Platforms agreed to adopt Qualcomm’s Dragonfly C1000 processors for its next-generation server fleet starting in the second half of 2028. The companies signed a multi-generation strategic agreement with extension rights, which tells traders this is designed as a long-term, expanding relationship, not a one-off order.

Qualcomm is also pushing hard into software. The planned acquisition of AI software firm Modular—valued at about $3.92B in stock in one report—aims to build an open, hardware-agnostic AI stack that runs efficiently across CPUs, GPUs, NPUs and custom ASICs. For QCOM, that means moving from “just chips” to a full platform that developers actually want to build on. The company also guided that its data center business should generate “billions” in revenue by fiscal 2027, giving traders something nearer-term to track instead of only 2029 targets.

This combo of raised guidance, real hyperscaler validation from Meta, and a deeper software story is why QCOM ripped roughly 9–11% to about $215.50 after the event and why Wells Fargo felt comfortable hiking its price target to $230 earlier in June 2026.

Conclusion

For active traders, QCOM just flipped from a mature handset name into a high-beta AI transition story. Qualcomm now has clear, quantified goals: $40B in non-handset revenue by 2029, more than $15B from data center AI, $10B from automotive, and non-GAAP EPS above $18. Add the Dragonfly C1000 CPU, AI300 accelerator, the Meta multi-generation deal starting 2H 2028, and the Modular acquisition, and you get a company trying to control both silicon and the AI software layer.

The market’s first reaction was loud. Qualcomm shares jumped around 9–11% to roughly $215.50, and the QCOM chart is showing strong support near $200 with traders buying dips. That doesn’t mean the path is straight up—long lead times, execution risk on the Meta rollout, and fierce AI competition remain real overhangs. But it does mean Qualcomm has put a credible growth blueprint on the table, and Wall Street is taking it seriously.

For short-term traders, QCOM is now a volatility vehicle tied to every new data center win, AI product update, or hyperscaler headline. For longer-term swing traders, it’s a textbook case of a legacy tech name trying to re-rate on a new story. As millionaire penny stock trader and teacher Tim Sykes, says, “Cut losses quickly, let profits ride, and don’t overtrade.”. As Tim Sykes loves to remind his students, “The market rewards preparation, not prediction—study the catalysts, study the chart, and let the price action confirm the trade.” QCOM’s new AI playbook is a catalyst worth studying, with strict risk management as always.

This is stock news, not investment advice. Timothy Sykes News delivers real-time stock market news focused on key catalysts driving short-term price movements. Our content is tailored for active traders and investors seeking to capitalize on rapid price fluctuations, particularly in volatile sectors like penny stocks. Readers come to us for detailed coverage on earnings reports, mergers, FDA approvals, new contracts, and unusual trading volumes that can trigger significant short-term price action. Some users utilize our news to explain sudden stock movements, while others rely on it for diligent research into potential investment opportunities.

Dive deeper into the world of trading with Timothy Sykes, renowned for his expertise in penny stocks. Explore his top picks and discover the strategies that have propelled him to success with these articles:

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* Results are not typical and will vary from person to person. Making money trading stocks takes time, dedication, and hard work. There are inherent risks involved with investing in the stock market, including the loss of your investment. Past performance in the market is not indicative of future results. Any investment is at your own risk. See Terms of Service here

The available research on day trading suggests that most active traders lose money. Fees and overtrading are major contributors to these losses.

A 2000 study called “Trading is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors” evaluated 66,465 U.S. households that held stocks from 1991 to 1996. The households that traded most averaged an 11.4% annual return during a period where the overall market gained 17.9%. These lower returns were attributed to overconfidence.

A 2014 paper (revised 2019) titled “Learning Fast or Slow?” analyzed the complete transaction history of the Taiwan Stock Exchange between 1992 and 2006. It looked at the ongoing performance of day traders in this sample, and found that 97% of day traders can expect to lose money from trading, and more than 90% of all day trading volume can be traced to investors who predictably lose money. Additionally, it tied the behavior of gamblers and drivers who get more speeding tickets to overtrading, and cited studies showing that legalized gambling has an inverse effect on trading volume.

A 2019 research study (revised 2020) called “Day Trading for a Living?” observed 19,646 Brazilian futures contract traders who started day trading from 2013 to 2015, and recorded two years of their trading activity. The study authors found that 97% of traders with more than 300 days actively trading lost money, and only 1.1% earned more than the Brazilian minimum wage ($16 USD per day). They hypothesized that the greater returns shown in previous studies did not differentiate between frequent day traders and those who traded rarely, and that more frequent trading activity decreases the chance of profitability.

These studies show the wide variance of the available data on day trading profitability. One thing that seems clear from the research is that most day traders lose money .

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Citations for Disclaimer

Barber, Brad M. and Odean, Terrance, Trading is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors. Available at SSRN: “Day Trading for a Living?”

Barber, Brad M. and Lee, Yi-Tsung and Liu, Yu-Jane and Odean, Terrance and Zhang, Ke, Learning Fast or Slow? (May 28, 2019). Forthcoming: Review of Asset Pricing Studies, Available at SSRN: “https://ssrn.com/abstract=2535636”

Chague, Fernando and De-Losso, Rodrigo and Giovannetti, Bruno, Day Trading for a Living? (June 11, 2020). Available at SSRN: “https://ssrn.com/abstract=3423101”