Goldman Sachs on Meta layoffs, cost-cutting, and delayed model releases: This isn't "cutting budgets to survive the winter," but "making room for new opportunities."

Goldman Sachs on Meta layoffs, cost-cutting, and delayed model releases: This isn't "cutting budgets to survive the winter," but "making room for new opportunities."

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Facing widespread concerns about Meta layoffs, reduced Reality Labs investment, and delayed release of foundational models, Goldman Sachs offers a different interpretation: this is not passive contraction under AI investment pressure, but a proactive strategic restructuring, reallocating resources from inefficient stock to high-value computing power demands, thus opening up space for long-term EPS upgrades.

According to multiple recent media reports, Meta's management may move forward with three major initiatives: large-scale layoffs and personnel restructuring, cutting Reality Labs department spending, and delaying the public release of its latest foundational model from its superintelligence lab. Amid ongoing ferment of these reports, Meta's stock price has dropped about 20% since the day after its Q4 earnings report on January 29, while the S&P 500 fell only about 7% in the same period.

Goldman Sachs analyst Eric Sheridan's team pointed out in its March 22 research report that none of the three actions actually exceed the forward-looking guidance framework provided by management in the most recent earnings call.

The more critical judgment: any cost-saving measures should be seen as Meta seeking a company-wide rebalancing of efficiency and growth — the freed resources will mainly be used for AI growth investments focused on computing power demand. The bank also stated that if these measures are implemented, Meta may return to its previous rhythm of "conservative guidance at the beginning of the year, with performance repeatedly upgraded throughout the year."

Goldman Sachs maintains its buy rating and 12-month target price of $835 for Meta, quantifying the potential impact of cost optimization on EPS through three scenario analyses. The core conclusion: Meta's existing cost structure is sufficiently flexible, and the rebalancing of efficiency and growth has the ability to continue driving positive EPS revisions.

Layoffs: Adjusting the personnel structure, not the overall scale orientation

According to Reuters, Meta is planning large-scale layoffs.

Goldman Sachs performed quantitative calculations in scenario one: assuming the total number of employees falls by 15% year-on-year by end of 2026, with 5% growth restored in both 2027 and 2028, and per capita non-depreciation/amortization costs growing about 6% annually. Under this scenario, compared to baseline Goldman forecasts, Meta's 2026 GAAP EBIT and earnings per share will see more than a 10% boost, while the boost in 2027-2028 can exceed 20%.

Goldman emphasizes that the essence of this scenario is not simply compressing personnel numbers, but reflects an increasingly obvious structural transformation trend in the industry since mid-December 2025: companies generally combine personnel adjustments with shifts towards AI and machine learning computing roles.

In other words, Meta's layoffs are more like "replacement" — substituting current positions with more tech professionals with AI backgrounds — rather than shrinking overall headcount. Goldman Sachs thus characterizes it as a proactive talent restructuring, rather than a passive cost-cutting response.

Reality Labs: Abandoning Horizon Worlds, not the entire spatial computing track

According to Bloomberg, Meta plans to adjust the core products of Reality Labs, which was interpreted by outsiders as a full withdrawal from that business unit.

Goldman Sachs believes this interpretation is biased, and cites multiple subsequent official Meta statements indicating: the core of this adjustment is cutting investment in traditional VR legacy products represented by Horizon Worlds, while the company remains highly invested in broader spatial computing ambitions and its strategic direction has not changed.

In scenario two, Goldman Sachs assumes annual Reality Labs spending cut by high single-digit to low double-digit percentages, with 10% of the savings reinvested into the business. Under this scenario, the potential boost to GAAP EPS from 2026 to 2028 is in the low to mid single-digit percentage range, with moderate flexibility but clear direction.

Goldman Sachs' judgment is: Meta is essentially lowering the priority of traditional VR within Reality Labs to free more resources toward AI integration and augmented reality (AR) directions.

Foundation model delay: the timeline has always been within expectations

The New York Times reported that the public release time of Meta's superintelligence lab's latest foundation model may be delayed.

Goldman Sachs responded that this timing has never exceeded its expectations. Considering the superintelligence lab was established in mid-2025 and has been around less than a year, compared to Google DeepMind, OpenAI, Anthropic, and other leading model institutions that have long experience, Meta needs at least 9 to 12 months to exhibit initial results in the public domain.

Goldman Sachs restates its anchor of Meta management’s public statements: the window for foundational model releases and AI strategic pillars (computing power layout, agent products, etc.) will mainly be in the second half of 2026 to 2027, and the first batch of models is only a starting point, to be iterated and evolved over multiple years.

The bank believes that judging Meta's superintelligence lab's progress pace by OpenAI and Anthropic expectations, given Meta's lab founding timeline, is itself a baseline bias.

Three scenario calculations: unlocking different paths of EPS flexibility

Goldman Sachs established three "blue sky scenarios" in the report to quantify the potential impact of different cost optimization paths on earnings, and clearly stated that none are baseline forecasts—actual outcomes are subject to multiple variable influences.

Scenario one (adjusting personnel scale and per capita costs) had the most significant boost effect, with potential increase in EPS for 2026 of over 10%, and more than 20% for 2027-2028.

Scenario two (cutting Reality Labs spending) showed limited flexibility, boosting three-year EPS in the low to mid single-digit percentage range.

Scenario three (zero growth in non-D&A operational spending over the next three years) theoretically had the greatest elasticity, potentially bringing a 30% boost to 2026 EPS, and a 40%-50% upside for 2027-2028, but Goldman Sachs identifies it as the least likely scenario—the main constraints including ongoing wage inflation for AI and machine learning roles, and projected staff increases over multiple years.

Goldman Sachs points out that Meta's current cost structure has ample profit flexibility, and any management measures aimed at balancing efficiency and growth investments have the potential to keep pushing EPS forecasts upward for years to come, rather than causing downward pressure.

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