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Snowflake (SNOW) reaffirmed its Q3 and FY26 guidance, which was originally provided in its Q2 earnings report on August 27, during an interview with a company executive that was posted on Instagram. The company reiterated expectations for Q3 Product Revenue of $1.125-$1.130 bln and a Non-GAAP operating margin of 9%, along with FY26 Product Revenue of $4.395 bln (+27% yr/yr) and the same 9% operating margin.

• The reaffirmation is giving another boost to SNOW shares, which are already up about 73% year-to-date and are now trading at multi-year highs.
• The confirmation of guidance follows an impressive Q2 report that showed Product Revenue growth accelerating to +32% yr/yr from +26% in Q1, while the net revenue retention rate held strong at 125%, highlighting robust customer expansion.
• The company continues to benefit from surging adoption of its AI-enabled tools, including Cortex AI and Snowpark, which had over 6,100 active weekly accounts and saw about 50% of new customers incorporating AI capabilities into their Snowflake deployments as of the end of Q2.
• Shares of other cloud data and analytics peers, including MongoDB (MDB) and DataDog (DDOG), are also trading higher in sympathy, reflecting renewed optimism in the cloud data platform space.

Briefing.com Analyst Insight:

SNOW’s reaffirmation of its Q3 and FY26 guidance underscores the company’s confidence in its near-term visibility and durable growth trajectory. The strength in Product Revenue and sustained high net revenue retention highlight a business that is successfully deepening customer engagement while broadening its AI-driven offerings. While the reaffirmation doesn’t raise expectations, it does validate the stock’s powerful YTD rally and signals management’s confidence heading into the back half of the fiscal year. The expanding use of Cortex AI and Snowpark indicates SNOW is solidifying its position as a key AI infrastructure player. That said, with the shares now trading at a premium multiple (1-year Forward P/E of 151x) and expectations running high, any slowdown in AI-related workloads could spark volatility.