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“The Buck Stops Here,”
Dylan Jovine, CEO & Founder
Behind the Markets
Just For You
Why Meta’s AI Chip Announcement Has Broadcom Investors Paying Attention
Author: Leo Miller. Posted: 3/18/2026.

Key Points
- Meta publicly confirmed Broadcom as its custom chip partner for the first time, removing lingering doubts about one of Broadcom’s most important AI relationships.
- The MTIA chip roadmap is expanding from ranking and recommendation into generative AI inference—a workload many expect to dominate AI compute by decade’s end.
- One notable gap in Meta’s announcement: no generative AI training chip, lending weight to reports that its most ambitious custom silicon project has been shelved for now.
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In a recent announcement, the Magnificent Seven tech giant Meta Platforms (NASDAQ: META) unveiled four customized artificial intelligence (AI) chips. The news follows semiconductor design behemoth Broadcom’s (NASDAQ: AVGO) earnings report, in which CEO Hock Tan specifically addressed Meta.
Meta’s announcement is a clear signal to Broadcom that could benefit AVGO. There are, however, some negatives to consider. What does this mean for Broadcom going forward?
META and AVGO Confirm MTIA Partnership
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Market watchers long suspected Meta was one of Broadcom’s custom AI processor customers, but Broadcom had not publicly identified Meta in that role until now. On Broadcom’s Q1 2026 call, Tan said, “Contrary to recent analyst reports, Meta’s custom accelerator MTIA road map is alive and well. We’re shipping now.”
MTIA, which stands for Meta Training and Inference Accelerator, is a family of custom chips developed in partnership with Broadcom. Tan’s comment followed reports that Meta had halted development of its most advanced custom AI training chip, codenamed Olympus.
Meta explicitly referenced Broadcom in its chip announcement, saying, “Meta Training and Inference Accelerator (MTIA), our family of homegrown AI chips developed in close partnership with Broadcom, has remained and will continue to be an important part of Meta’s AI infrastructure strategy.”
While markets had already assumed the partnership, the mutual acknowledgement from both companies removes any lingering doubt.
The Good: META-AVGO Partnership Expands Into GenAI
The title of Meta’s post, “Four MTIA Chips in Two Years: Scaling AI Experiences for Billions,” supports the bullish scenario Broadcom outlined in its earnings. Hock Tan noted that many customers are developing two custom chips per year with Broadcom—exactly the pace Meta described—lending credibility to Broadcom’s statements and suggesting deeper customer relationships.
Meta is using MTIA for multiple purposes, including training and inference for its ranking and recommendation (R&R) models. Training develops more capable models, while inference deploys those models to answer questions and perform tasks.
R&R training and inference help Meta deliver more engaging content and better-targeted ads across its services. Meta’s apps reach about 3.5 billion users—more than 40% of the world’s population—so the company has large and growing compute needs that it is relying on Broadcom to meet.
The MTIA lineup also extends beyond R&R. Meta plans to use MTIA 450 and MTIA 500 for GenAI inference, with mass deployments expected in 2027. GenAI inference likely includes chatbot queries, image and video generation, and AI-powered business agents in WhatsApp.
Although experts do not generally consider Meta’s LLaMa models state-of-the-art compared with ChatGPT, Claude, or Gemini, they can still be useful and monetizable. Meta AI already has over 1 billion users, creating an opportunity to generate revenue from these models.
For Broadcom, MTIA’s expansion from R&R into GenAI inference is positive: supporting both Meta’s core workloads and emerging ones should translate to more chip sales.
The Bad: META-AVGO GenAI Training Chip Takes a Back Seat
Meta’s announcement did not include a GenAI training chip, which adds weight to reports that Meta has scaled back Olympus development. Meta’s Chief Financial Officer, Susan Li, recently said Meta “expects” and is “hopeful” it can expand its use of custom silicon to train AI models “eventually.”
This is a negative for Broadcom, which would likely have co-developed Olympus. Meta has not abandoned training ambitions, but the timeline for Broadcom to earn meaningful revenue from that project may have lengthened.
AVGO and META: Powering the Growth in AI Inference
Overall, Meta’s relationship with Broadcom is now confirmed and appears to be growing significantly outside of GenAI training.
Many expect inference to overtake training as the dominant AI workload in the coming years. McKinsey predicts that inference will grow at a compound annual rate of about 35% over the next five years and account for more than half of AI compute by 2030.
That outlook supports Broadcom’s strategy: its deepening relationship with Meta—especially around inference workloads—should help drive future growth.
Additional Reading from MarketBeat.com
Data Storage to Data Intelligence: Everpure’s Big AI Era Rebrand
Reported by Leo Miller. Article Published: 3/16/2026.
Everpure (NYSE: PSTG), the tech companyformerly known as Pure Storage, has become a major beneficiary of the artificial intelligence (AI) data-center boom. Over the past three years, shares have gained more than 150%. Still, the stock has experienced significant volatility: in nine of Everpure’s last 12 earnings releases, shares moved at least 10% the following day — four times up and five times down.
After the company’s latest report, Everpure took a hit, with shares falling about 10% despite beating estimates and issuing stronger-than-expected guidance.
On one hand, Everpure is reporting strong and accelerating growth, having just reached $1 billion in quarterly revenue for the first time. On the other hand, rising memory-chip prices and strategic shifts are clouding the company’s outlook.
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Key Points
- Pure Storage has changed its name to Everpure as it shifts its business from data storage to an intelligent data management platform.
- The company’s accelerating revenue and hyperscaler engagements are key areas of strength.
- However, spiking memory chip prices are putting pressure on gross margins, creating uncertainty going forward.
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Below we break down those dynamics to provide an updated perspective on Everpure.
PSTG cements shift into data management and intelligence as Everpure
It’s important to understand why Everpure changed its name from Pure Storage: the rebrand signals the company’s strategic trajectory. The firm began as a provider of high-performance data-storage hardware; its all-flash systems delivered substantial speed and efficiency gains over traditional hard-disk storage.
Everpure’s Purity operating environment provides a unified platform for managing its storage products, and the company’s hardware and software are designed to be upgradable. Customers can upgrade a storage array repeatedly as technology improves rather than buying a completely new system — an early focus that justified the Pure Storage name and helped the company gain share in the enterprise market.
Everpure says it has gained 13% market sharesince 2013, while legacy competitors like Dell Technologies (NYSE: DELL) and International Business Machines (NYSE: IBM) have lost meaningful share.
Over time, the company has layered software and services on top of its hardware to transition from a storage vendor toward a broader data-management platform. The announced acquisition of 1touch, which accompanied the name change, underscores this shift: Everpure says 1touch will help customers “better understand the meaning of their data and unlock its strategic value through AI and other applications.”
In short, Everpure is positioning itself to do more than store data — it wants to help customers use data to power AI and analytics. Removing “storage” from the corporate name is a signal that the firm is moving toward a fuller data-management and intelligence offering, which could let it capture a larger slice of the enterprise AI market.
Revenues soar, but memory-chip shortage weighs on PSTG
Many parts of Everpure’s business are trending positively. Revenue grew by more than 20% in the latest quarter, outpacing estimates and accelerating for five quarters in a row. The company’s midpoint revenue-growth guidance of 19% for fiscal 2027 also topped expectations. Everpure counts Meta Platforms (NASDAQ: META) as a large customer and is in discussions with other hyperscalers.
However, memory chips are a major cost input, and component prices have surged amid the current shortage. That creates margin uncertainty: next quarter the company expects product gross margin at the lower end of its typical 65%–70% range.
Management expressed confidence that gross margins will improve through the year but cautioned that pricing visibility in the memory market is “non-existent.” That uncertainty has investors concerned that the margin outlook may be optimistic.
Everpure is taking steps to mitigate the impact. It recently implemented a 20% price increase and left open the possibility of further hikes. In addition, when hyperscalers contract with Everpure they frequently purchase memory components directly from suppliers, which limits Everpure’s exposure to some price moves. Nevertheless, gross-margin uncertainty was a key reason the stock declined sharply after the earnings release despite strong top-line results.
AI demand is a double-edged sword for PSTG
AI demand is clearly driving customer interest, but it has also contributed to the memory-chip shortage that currently acts as a headwind for Everpure.
The business has momentum, and the potential to add more hyperscaler customers represents a meaningful upside catalyst. The company’s shift toward broader data solutions could allow it to sell a more comprehensive suite of products as enterprise AI adoption expands.
That said, memory cost pressures could continue to weigh on margins and share price. The stock trades at a forward price-to-earnings ratio of roughly 26x, more than 10% below its three-year average near 31x.
The MarketBeat consensus price target on Everpure sits near $94.50, a level that implies upside of more than 50%. After the earnings print, most analyst updates tracked by MarketBeat were price-target increases; however, the simple average price target among analysts moved only slightly from $78.50 to $78.75. While that average is well below the consensus target, it still implies substantial upside of over 25% from current levels.
Overall, Everpure is not a low-risk investment, but it could deliver significant long-term gains if its strategy of combining data storage with data intelligence continues to gain traction.
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