Title

Earning Preview: Snowflake this quarter’s revenue is expected to increase by 31.25%, and institutional views are bullish

Abstract

Snowflake will report fiscal fourth-quarter results on February 25, 2026 Post Market, with attention on year-over-year growth in revenue and adjusted EPS, the trajectory of margins, and execution in recently announced AI initiatives and partnerships.

Market Forecast

For the fiscal fourth quarter, Snowflake’s internal projection set from its prior update points to total revenue of 1.25 billion US dollars, adjusted EPS of 0.27, and EBIT of 92.42 million US dollars; on a year-over-year basis, these translate to growth of 31.25% for revenue, 56.10% for EPS, and 126.75% for EBIT. Forecasts for gross margin or net margin were not provided; if published, those would refine expectations for profitability this quarter.

Snowflake’s main business remains centered on product consumption revenue, with ongoing growth supported by usage expansion among large accounts and progress in data application workloads on the platform. The most promising segment is the AI-enabled data applications under the product umbrella, anchored by last quarter’s product revenue of 1.16 billion US dollars and company-wide year-over-year revenue growth of 28.75%; AI feature rollouts and enterprise deployments signal further momentum into the current quarter.

Last Quarter Review

Snowflake delivered last quarter revenue of 1.21 billion US dollars, a gross profit margin of 67.77%, a GAAP net loss attributable to the parent company of -0.29 billion US dollars with a net profit margin of -24.24%, and adjusted EPS of 0.35 (up 75.00% year over year), alongside a quarter-on-quarter growth rate of GAAP net profit of 136%.

A notable highlight was the outperformance versus expectations: revenue exceeded the prior estimate by 31.20 million US dollars and EBIT surpassed estimates by 22.65 million US dollars, supporting confidence in consumption dynamics and operating leverage. By business line, product revenue reached 1.16 billion US dollars, while professional services and other contributed 54.53 million US dollars; total company revenue growth was 28.75% year over year, underscoring resilient usage trends.

Current Quarter Outlook

Core Product Consumption and Revenue Quality

Product consumption remains the central driver of Snowflake’s quarterly performance, and the latest forecast implies total revenue of 1.25 billion US dollars, up 31.25% year over year. The consumption model’s sensitivity to workload intensity and data processing volume suggests revenue can track close to customer usage patterns, especially as existing customers expand applications and integrate more complex analytics. With adjusted EPS forecast at 0.27 and EBIT forecast at 92.42 million US dollars, the company’s P&L should reflect continued operating efficiency, though gross margin outcomes will depend on workload mix and platform resource utilization.

Quarter-to-quarter performance is often influenced by large account expansions and seasonal usage characteristics, and the prior quarter’s beat on both revenue and EBIT provides a constructive baseline. The quarter-on-quarter growth rate of net profit at 136% last quarter indicates progress in narrowing losses on a GAAP basis despite elevated investment in growth, suggesting that cost discipline and scale benefits are taking hold. If usage growth remains robust across enterprise cohorts, revenue quality—measured through sustained consumption and broad-based customer engagement—should support the revenue and EPS trajectory outlined in the forecast.

AI and Data Applications Momentum

Recent announcements and product developments since January strengthen the case for accelerating AI-enabled workloads. Snowflake unveiled Cortex Code and Semantic View Autopilot in early February, expanding the AI suite to help enterprises automate data engineering, analytics, and governance tasks, and to enable agent-building without the need for extensive coding. These capabilities, packaged within Snowflake’s AI product suite, can increase workload intensity on the platform by making it easier for teams to stand up data applications that directly consume platform resources.

The multiyear, 200 million US dollars partnership with OpenAI integrates advanced models across major cloud providers into Snowflake’s Data Cloud, enabling customers to query and build agents using plain language and work with multimodal data securely. This collaboration targets practical enterprise use cases by connecting organizational data to AI models under governance, which can raise consumption as customers deploy these agents to production use. The Wolfspeed deployment to expand Snowflake usage for AI across operations exemplifies how industrial and manufacturing contexts are adopting these tools to streamline processes and improve decision-making with real-time telemetry and analytics.

The acquisition of Observe, announced in January, adds observability capabilities that allow enterprises to collect, store, and analyze full-stack telemetry more effectively within Snowflake. By bringing observability data directly into the platform, customers can unify data across applications, infrastructure, and security events—creating new, high-frequency workloads that feed product consumption. Together, these developments underpin the “most promising segment” thesis: AI-enabled data applications within the product umbrella are poised to compound consumption, building on last quarter’s 1.16 billion US dollars in product revenue and the company’s 28.75% year-over-year growth baseline.

Key Stock Price Drivers This Quarter

The stock’s reaction around the February 25, 2026 report will likely hinge on three tangible drivers: the revenue growth rate versus forecast, the adjusted EPS trajectory, and signals on AI adoption and monetization. The 31.25% year-over-year revenue forecast sets a clear benchmark; upside would likely require evidence of accelerated consumption from AI-related workloads and data applications beyond core analytics. With adjusted EPS forecast at 0.27 (up 56.10% year over year), investors will look for operating-expense discipline and scale efficiencies that translate usage growth into earnings momentum.

Qualitative indicators will matter, too. The cadence of AI product releases (Cortex Code and Semantic View Autopilot), enterprise deployment updates (such as Wolfspeed’s expansion), and the OpenAI partnership can provide visibility into pipeline durability. Management’s commentary on customer adoption, agent-driven workloads, and observability integration from Observe can signal whether AI features are reaching broader production usage and sustaining data-processing intensity. If these signals are strong, they should reinforce confidence in translating AI initiatives into product consumption and revenue growth throughout the next fiscal periods.

Finally, while the company has demonstrated outperformance versus estimates in the prior quarter, margin commentary will be scrutinized in the absence of explicit margin forecasts. Investors will watch for any updates on gross margin drivers (workload mix and platform efficiencies) and net margin improvement strategies to gauge the durability of the EPS path. Demonstrable progress on operating leverage, together with high-quality revenue growth patterns, would be supportive of positive stock reactions.

Analyst Opinions

Bullish opinions dominate the institutional landscape in the period from January 1, 2026 to February 18, 2026. Notably, Bank of America reiterated a Buy rating with a 275.00 US dollars target and highlighted Snowflake as a top infrastructure software pick for 2026, emphasizing its role in enabling enterprise AI and advanced analytics. Mizuho reiterated a Buy with a 285.00 US dollars target, citing strong growth potential and ongoing product momentum that can drive sustained consumption and earnings scalability. RBC maintained an Outperform rating while trimming its target to 245.00 US dollars, pointing to healthy demand supported by bookings and guidance cadence despite near-term target adjustments.

These bullish views collectively argue that Snowflake’s AI product suite and recent innovation cadence are increasingly tied to enterprise workloads likely to lift platform consumption. The introduction of Cortex Code and Semantic View Autopilot serves practical enterprise needs by automating complex data engineering tasks and improving governance, which can accelerate adoption without prohibitive resource requirements. The multiyear OpenAI partnership—budgeted at 200 million US dollars—provides a pathway for organizations to integrate large language models and multimodal capabilities directly with their governed data, simplifying agent deployment and encouraging production use cases that increase data processing on Snowflake.

Analysts also point to enterprise validations in manufacturing and operations, such as Wolfspeed’s expansion of Snowflake usage to deploy AI across factory, supply chain, and enterprise domains, as evidence of durable AI-driven workload expansion. Pairing these deployments with the Observe acquisition gives Snowflake a more comprehensive telemetry and observability story, enabling customers to consolidate data and accelerate root-cause analysis, anomaly detection, and performance optimization. In this context, bullish institutions expect that the current quarter’s forecast—revenue of 1.25 billion US dollars and adjusted EPS of 0.27—could be supported by AI-enabled workloads, continued product-led consumption, and improving operating efficiency.

In framing the quarter, bullish institutions emphasize that the prior quarter’s beat on revenue and EBIT established a constructive setup, and the company’s reported adjusted EPS growth of 75.00% year over year demonstrates the potential for earnings leverage as scale increases. They will look for confirmation that the pipeline of AI features translates into broader usage across existing customers, which can underpin the 31.25% revenue growth forecast and the 56.10% adjusted EPS growth outlook for the quarter. Should management’s commentary substantiate rapid enterprise adoption of AI agents, automated data engineering tools, and observability integration, the bullish majority expects the stock to respond favorably to the print and guide.