Meta is a stock that our firm is watching this year with great anticipation. The headline results are good and important to review, yet what’s most important is what is up ahead as Meta begins to merge LLMs directly into their recommendation systems, a shift away from back-end optimizations based on algorithms. This is how management described the shift: “Our feeds will become more interactive overall. Today, our apps feel like algorithms that recommend content. Soon, you'll open our apps, and you'll have an AI that understands you and also happens to be able to show you great content or even generate great personalized content for you.”
There are many advertising businesses using AI, yet there is something unique about how Meta is approaching the problem – and this is showing up in the results. Per our Q1 2026 Top 15 AI Stocks report: “Margins matter, cash matters, but what matters more is the 3X growth Meta has seen in its Advantage+ segment in less than a year, as the company had reported $20 billion about three quarters ago, with the recent update from last quarter at $60 billion. If this runaway growth continues, then Meta will easily be outpacing Search and Google Cloud combined on AI revenue.”
That “something unique” is Meta’s data. What does Search really know about you other than intent? Meanwhile, Meta offers rich contextual, behavioural data that expands over time. The dataset offers preferences, emotions, social context, network effects, etc, whereas Google would struggle to truly “know you.” This can make the LLMs more personal and effective especially as we enter the agent era. Notably, this is not an either/or discussion about Google Search, rather it’s an opportunity to discuss Meta’s strengths and why the company is currently number two in AI revenue despite spending a less capex than its counterparts.
Below, I discuss the earnings call discussions that were centered around the plans Meta has for 2026 and also the numbers that drove strong after hour performance.
Meta to Replace Legacy, Rule-Based Algorithms with AI Agents
Meta is an “eyeballs” company, and thus, an important lever to growth is increasing user engagement. In the most recent quarter, the company drove incremental engagement from ranking and product improvements. Primarily, the company optimized their systems to consider longer interaction histories to better identify a person’s interests. This led to the highest lift in feed views that the company has seen in two years: “The optimizations we made in Q4 drove a 7% lift in views of organic feed and video posts on Facebook, resulting in the largest quarterly revenue impact from Facebook product launches in the past two years.”
Moving forward, Meta’s goal this year is to scale their training data to offer more personalized recommendations. By moving away from algorithms driving the feeds to LLMs, Meta can make he systems more responsive to real-time interest.
This may seem like a subtle shift, but it’s actually not subtle at all – Meta is proposing a complete overhaul in how their systems surface content. Moving forward, LLMs will offer reasoning for a level of personalization not possible in the current approach, which is more pattern recognition based. Think of how Spotify works – it surfaces music you’ve already listened to. Facebook feeds are similar. However, moving forward, Meta can offer a personalized agent approach to where AI optimizes a feed to suggest content that does not require a direct signal.
Here is what was stated on the call:
“We're seeing in our early testing that personalized responses drive higher levels of engagement, and we expect to significantly advance the personalization of Meta AI this year. This dovetails with our investments in content understanding, which will enable our systems to develop a deeper understanding of each person's interests and preferences while also identifying the most relevant content across our platform to pull into responses.”
Although Meta uses AI in its recommendations, the current systems are based on pattern and behavior-driven algorithms. For 2026, Meta will offer content that goes beyond the bounds of what you’ve already searched for/engaged with AI agents that can more intelligently infer your interests.
The result will be more time spent on the platform and with higher engagement. Even incremental gains here will lead to more advertising dollars.
Ad Platform Driven by Superintelligence
The second area that Meta is making “big bets” is the increasing monetization efficiency. Last quarter alone, the company doubled the number of GPUs used to train their GEM model for ads ranking. Similar to what was stated above, part of the improvements is using longer sequences of user behavior to inform the feed plus which ads are placed and when: “This new sequence learning architecture is significantly more efficient than our prior architectures which should enable us to further scale up the data, complexity and compute we use in our future ranking models to deliver performance gains.”
Meta’s main approach to increasing the effectiveness of ad placements remains user targeting, but just smarter user targeting. This results in 4X better results than using AI to increase overall ad load: “In fact, in the second half of 2025, our initiatives on Facebook to redistribute ads across users and sessions delivered a nearly 4x larger revenue impact than Facebook ad load increases.”
As you’ll see below in the Financials section, these improvements are making a material difference with Q4 revenue growing 17% QoQ and with a forward guide that implies the highest YoY growth rate for Meta since Covid-fueled 2021.
Driving Down Costs:
There are two primary ways that Meta plans to drive down costs. The first is to leverage AI internally to reduce their workforce.
Here is what was stated about using AI internally to replace engineers: “Since the beginning of 2025, we've seen a 30% increase in output per engineer with the majority of that growth coming from the adoption of agenetic coding, which saw a big jump in Q4. We're seeing even stronger gains with power users of AI coding tools, whose output has increased 80% year-over-year. We expect this growth to accelerate through the next half.”
The second is to use a mix of custom chips, lower-cost AMD GPUs and Nvidia GPUs to achieve their goals: “Procuring sufficient infrastructure capacity is central to these initiatives, and we're working to meet our silicon needs by deploying a variety of chips that optimally support each of our different workloads. To that end, in Q4, we extended our Andromeda ads retrievable engine, so it can now run on NVIDIA, AMD and MTIA. This, along with model innovations, enabled us to nearly triple Andromeda's compute efficiency. In Q1, we will extend our MTIA program to support our core ranking and recommendation training workloads in addition to the inference workloads it currently runs.”
The paragraph above spells out headwinds to Nvidia to where even if the market continues to grow, Nvidia’s overall percentage of the market will erode. We covered this in the Q3 2025 Top 15 AI Stocks report under the subheading “AI is Diversifying”
Financials
By Royston Roche
Q1 Revenue guide suggests fastest growth since Sept 2021
Q4 revenue grew by 23.8% YoY and 16.9% QoQ to $59.9 billion, beating estimates by 2.4%. Although strong sequential growth in Q4 is seasonal and Meta posted a 19.2% QoQ increase in Q4 2024, the current sequential growth is being achieved on a substantially higher revenue base of $51.2 billion versus $40.6 billion in the prior-year period. The strong revenue growth was primarily driven by robust demand stemming from AI advancements in ad recommendations, monetization, and user engagement.
Management issued strong revenue guide of $53.5 billion to $56.5 billion, implying a 30% YoY growth and a sequential decline of (8.2%) at the midpoint. While the QoQ contraction reflects normal seasonality, the implied 30% YoY growth represents the fastest pace in the last 4.5 years.
The company’s 2025 revenue grew by 22.2% YoY to $200.97 billion. Looking ahead, revenue growth is expected to accelerate 2.8 percentage points to 25% YoY growth to $251.3 billion in 2026 and will moderate to 16.9% YoY to $293.8 billion in 2027.
Record Q4 Advertising Revenue of $58.1 billion
Meta is already seeing tailwinds from AI recommendation models driving higher ROI for advertisers following increased time spent across its family of apps.
Q4 advertising revenue grew by 24.3% YoY to a record $58.1 billion. Notably, absolute advertising revenue growth reached $11.3 billion in the quarter, surpassing the $10.2 billion increase recorded in Q3.
Key Metrics
Q4 ARPP reaches a record $16.56
Perhaps the most important metric for Meta’s ad monetization is Family ARPP (average revenue per person). It reached a record $16.56 in Q4 2025, highlighting that Meta’s AI-driven ad performance improvements and monetization efforts are bearing fruit. While the 16.2% YoY growth in Q4 reflects a deceleration from the 17.7% seen in Q3, such a trend is common on a higher base and less of a concern given Meta is guiding for a modest acceleration this fiscal year. Notably, Q4 ARPP outpaced the 15.6% growth recorded in the prior-year period.
In Q4, the total number of ad impressions grew by 18% YoY, accelerating from 14% growth in Q3 and up from 6% in the year ago quarter. Impression growth was broad-based across regions, driven primarily by higher engagement and user growth, with incremental support from ad load optimizations.
Pictured Above: Ad impressions saw outsized growth this past quarter due to the new sequence learning architecture discussed above. Source: Meta investor relations.
The average price per ad continues to rise and it grew by 6% YoY in Q4, benefiting from increased advertiser demand, largely driven by improved ad performance. However, the YoY growth has decelerated from 10% in Q3 and 9% in Q2 and this metric is to be watched despite ad impressions offsetting the deceleration.
Family of Apps daily active people (DAP) grew by 6.9% YoY to 3.58 billion in Q4, though the growth rate decelerated slightly from 7.6% growth in Q3.
Margins
Meta delivered a sequential improvement in operating margin in Q4 as its continued investments in AI are beginning to show early signs of payoff, even though margins were lower than a year ago quarter.
- Q4 gross margin was 81.8%, up 10 basis points YoY and down 20 basis points sequentially.
- Q4 operating income increased 5.9% YoY to $24.7 billion, with an operating margin of 41.3%. The margin improved by 130 basis points sequentially, but declined 700 basis points from a year ago, largely due to higher AI-related operating expenses.
- Looking ahead to 2026, management expects total expenses to grow by 40.6% YoY to $165.5 billion—driven largely by increased infrastructure spending and continued investment in AI talent. Even with those higher costs, the company still expects operating income to grow in 2026. Management also emphasized that losses at Reality Labs are not expected to increase next year.
- Q4 net income grew by 9.3% YoY to $22.77 billion with a net profit margin of 38% compared to 43.1% in the same period last year.
GAAP EPS beat of 8%
Q4 GAAP EPS grew by 10.7% YoY to $8.88, beating estimates by 8%, driven primarily by higher revenue from stronger AI monetization. Analysts expect EPS to grow 2.4% YoY to $6.59 in Q1 2026 and down (0.3%) YoY to $7.12 in Q2 2026.
Looking ahead, GAAP EPS is expected to grow 26.5% YoY to $29.71 in 2026 and 16.3% YoY to $34.55 in 2027.
Cash Flow and Balance Sheet
Meta’s cash flows improved in Q4 driven by higher profits.
- Q4 operating cash flow grew by 29.4% YoY to $36.2 billion with an operating cash flow margin of 60.5% compared to 57.8% in the same period last year.
- Q4 free cash flow grew by 7% YoY to $14.1 billion with a free cash flow margin of 23.5% compared to 27.2% in the same period last year. Q4 capex grew by 49.2% YoY to $22.14 billion. 2025 capex grew by 84.1% YoY to $72.22 billion. Management expects 2026 capex to be $115 billion to $135 billion, implying a YoY growth of 73.1% at the midpoint primarily due to higher AI investments.
- The company had cash & marketable securities of $81.6 billion and debt of $58.7 billion compared to $44.45 billion and $28.8 billion at the end of Q3. The company issued debt of $30 billion in Oct 2025. Meta also entered a joint venture with Blue Owl Capital to fund its development at the Hyperion data center in Louisiana. Thereby, helping it to keep about $27 billion in debt off-balance sheet, where it would sit in a special-purpose vehicle tied to Blue Owl. While this approach may improve reported leverage and financial ratios, it carries inherent risks as the company is indirectly responsible for the off-balance sheet debt.
Conclusion
Meta was able to put up strong results primarily by increasing ad impressions, despite seeing a decelerating average price per ad from 14% growth last year to 6% growth this year. The combination resulted in average price per person reaching $16.56 up from $14.25 in the year ago quarter.
Facebook feeds saw an improvement in its sequencing learning architecture. In other words, Meta tracks user history longer to infer context on what the user is most interested in seeing next, which led to higher user engagement and a spike in ad impressions. Early signs of this improvement are evident with a forward guide that implies the highest YoY growth rate for Meta since 2021 at 30% YoY growth guided for Q1.
Most importantly, management is stating there will be a substantial shift to their underlying recommendation systems by re-architecting its traditional algorithms that are more pattern-based to now become more intuitive and forward-thinking in terms of anticipating what a user will want to see next.
Royston Roche, Equity Analyst at I/O Fund contributed to this analysis.
Please note: The I/O Fund conducts research and draws conclusions for the company’s portfolio. We then share that information with our readers and offer real-time trade notifications. This is not a guarantee of a stock’s performance and it is not financial advice. Please consult your personal financial advisor before buying any stock in the companies mentioned in this analysis. Beth Kindig and the I/O Fund own shares in META at the time of writing and may own stocks pictured in the charts.
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