tapebrief
SNOW · Q2 2026
SNOW · Q4 2026

SNOW · Q3 2026 Earnings

Bullish

Snowflake

Reported December 3, 2025

30-second summary

Snowflake beat its Q3 product revenue guide by ~$28M ($1.158B vs. $1.125–1.130B guided), with product growth of 29% YoY — a modest deceleration from Q2's 32% but still well ahead of the 25–26% guided. Management raised FY26 product revenue to $4.446B (+28% YoY, up from $4.395B/+27%) and disclosed the first hard AI revenue milestone: a $100M run rate hit one quarter early, with AI influencing 50% of Q3 bookings. The print is clean, but the Q4 operating margin guide of 7% — 400bps below Q3's 11% actual — is the one tension worth flagging.

Headline numbers

EPS

Q3 FY2026

$0.35

Revenue

Q3 FY2026

$1.21B

+28.7% YoY

Gross margin

Q3 FY2026

67.7%

Free cash flow

Q3 FY2026

$0.11B

Operating margin

Q3 FY2026

-27.2%

Key financials

Q3 FY2026
MetricQ3 FY2026YoYQ2 FY2026QoQ
Revenue$1.21B+28.7%$1.15B+5.9%
EPS$0.35—$0.35+0.0%
Gross margin67.7%—73.0%-530bps
Operating margin-27.2%—11.0%-3820bps
Free cash flow$0.11B—$0.06B+96.6%

Guidance

Snowflake beat Q3 FY2026 guidance across revenue and margins, raising full-year product revenue by 1.2% to $4.446B (+100 bps growth), but Q4 guidance signals margin compression to 7% from Q3's 11%.

Guidance is issued for both next quarter and the full year. Both may appear below.

Actuals vs prior guidance

MetricPeriodPrior guideActualΔResult
Product RevenueQ3 FY2026$1,125 - $1,130 million$1,158 million+$28-33M above guideBeat
Product Revenue YoY GrowthQ3 FY202625-26%28.6%+2.6 pts above guideBeat
Operating Income Margin (Non-GAAP)Q3 FY20269%11%+200 bps above guideBeat

New guidance

MetricPeriodGuideYoY
Product RevenueQ4 FY2026$1,195 - $1,200 million27%
Operating Income Margin (Non-GAAP)Q4 FY20267%—

Changes to prior guidance

MetricPeriodPrior guideNew guideΔResult
Product Revenue
FY2026
$4,395 million$4,446 million+$51M (+1.2%)Raised
Product Revenue YoY Growth
FY2026
27%28%+100 bpsRaised

Reaffirmed unchanged this quarter: Product Gross Profit Margin (Non-GAAP) (75%), Operating Income Margin (Non-GAAP) (9%), Adjusted Free Cash Flow Margin (Non-GAAP) (25%)

Segment performance

Q3 FY2026
SegmentQ3 FY2026YoY
Product Revenue$1.158B+28.6%
Professional Services and Other Revenue$0.055B+30.4%

Platform metrics

Q3 FY2026
SegmentQ3 FY2026
Net Revenue Retention Rate125%
Customers with Trailing 12-Month Product Revenue > $1M688
Forbes Global 2000 Customers766
Remaining Performance Obligations (RPO)$7.88B
RPO Year-over-Year Growth37%

Profitability

Q3 FY2026
SegmentQ3 FY2026
Product Gross Margin (Non-GAAP)76%
Operating Margin (Non-GAAP)11%
Adjusted Free Cash Flow Margin11%

Management tone

Q1 FY26 anchor → Q2 FY26 anchor → Q3 FY26 anchor: "AI as foundational pillar" → "AI as logo-acquisition engine" → "AI as quantified revenue stream."

AI disclosure crossed the dollar threshold for the first time. Last quarter management defended its refusal to break out AI revenue, framing it via "influence" metrics. This quarter Sridhar disclosed a hard number in prepared remarks: "$100M AI revenue run rate achieved one quarter early." That single disclosure resets the bull/bear debate — the AI contribution is no longer an unquantified narrative. Combined with Sridhar's claim that "Snowflake Intelligence saw the fastest adoption ramp in Snowflake history" and 1,200 customers on Snowflake Intelligence specifically, the framing has hardened from soft influence to hard consumption.

The "beat plus more" guide pattern is moderating. Two quarters ago Mike characterized Snowflake as having "consistently been raising by the beat plus more for the last six quarters." This quarter the FY raise of $51M roughly equals the ~$28M Q3 beat plus the implied tailwind from a stronger Q4. The pattern still holds directionally, but the magnitude has compressed alongside the underlying beat — Q2's $50M beat became a $70M FY raise; Q3's $28M beat became a $51M FY raise.

Management is now spending against AI conviction. The $200M Anthropic commitment is the largest single capital signal in two quarters. Sridhar explicitly framed it in Q&A as Snowflake "buying Anthropic models" — i.e., a confidence signal that AI consumption demand will support the inventory. This is a notable escalation from Q1, when AI was discussed as a "foundational pillar" with no equivalent capital commitment, and from Q2, when the discussion was about influence on bookings rather than buy-side commitment to model capacity. The Q4 margin compression to 7% appears to be partially funding this.

The competitive narrative has expanded from "best AI data platform" to "platform breadth." Q2's Sridhar quote was assertive on AI positioning ("the best AI data platform"); this quarter the framing has widened. The OpenFlow callouts, the zero-copy data sharing answer to Barclays' Raimo Lenschow, and the "soup to nuts" framing in the Evercore exchange all position Snowflake as the centralized data hub across an expanding product surface. Sridhar's claim that zero-copy is "complementary" rather than competitive — anchored by named agreements with ServiceNow, Salesforce, SAP, and Workday — is the most substantive new piece of competitive evidence.

Q&A highlights

Sanjit Singh · Morgan Stanley

Asked Brian to explain why Q3 product revenue beat guidance by only ~3% despite being described as strong, yet Q4 guidance represents the best sequential guide in years. Also asked Sridhar about types of customers adopting AI products, specific use cases for Snowflake Intelligence, and Cortex AI adoption details.

Brian explained the quarter played out as expected with only ~$1-2M impact from hyperscaler outage; emphasized FY guidance raise of $51M to $4.446B is the most meaningful signal of business fundamentals. Sridhar detailed how Snowflake Intelligence unlocks data access for business users, providing examples from USA Bob's, Fanatics, ServiceNow, and TS Imagine; emphasized the product democratizes data access beyond analysts.

Q3 revenue beat ~3%, largely as expectedHyperscaler outage impact: $1-2M revenueFY26 guidance raised by $51M to $4.446B (28% YoY growth)7,300+ accounts using AI capabilities weekly

Kirk McGrane · Evercore ISI

Asked whether Snowflake is now landing new customers with multiple products simultaneously (beyond just core data warehouse) given AI capabilities, and whether this expands the sales surface area for new logos.

Sridhar confirmed AI products now play key role in new logo pitches, enabling hyper-customized POCs with synthetic datasets. However, emphasized landing still starts with core data warehouse value prop. Lower-stack products like OpenFlow also driving adoption by improving data ingestion efficiency, expanding aperture from 'analytics provider' to 'soup to nuts' data platform.

AI products enabling customized POCs and synthetic data demos for new logosOpenFlow gaining adoption for data ingestion efficiencyProduct portfolio spans OpenFlow → Snowpark → analytics engine → ML → AILanding remains anchored in core data warehouse value, then expanding into multiple products

Brent Pill · Jefferies

Asked when AI bookings deals will transition to go-lives and revenue recognition, and whether this will drive acceleration in FY27. Also asked clarification on the $200M Anthropic partnership structure and backlog treatment.

Sridhar noted go-lives are already happening as evidenced by Q4 guidance beat and raise; consumption trends drive forecasts. Company tracking use case wins, implementation duration, and go-live timing. Emphasized AI partnerships accelerate go-lives. Brian clarified $200M Anthropic commitment is on buy-side (Snowflake purchasing from Anthropic), demonstrating confidence in AI revenue growth; it is not a backlog item but rather operational capex/expense.

Q4 guidance represents 'pretty hefty beat and raise' driven by consumption trendsCompany using ML models to forecast and track go-live timingAI products accelerating use case implementation timelines$200M Anthropic partnership is Snowflake buying Anthropic models (not backlog)

Dan Dellinger · Deutsche Bank

Asked Sridhar about impact of data migrations on product revenue this quarter vs. last quarter, sustainability of cloud migration momentum, and whether migrations are being accelerated by AI. Also asked Brian to explain why Q4 operating margin guidance is lower than Q3 actual and prior year FY26 guidance.

Sridhar noted migrations are early stage (15-20% penetration per AWS), with AI playing dual role as both 'pull' (increasing data value) and 'push' (accelerating migration speed). Tuck-in acquisitions like Datometry improve migration velocity. Company continuously monitoring migration lifecycle. Brian noted Q4 margin guidance requires no special interpretation; decline is typical and not indicative of underlying trends.

Data migrations at 15-20% penetration (per Matt Garman statement)AI accelerating migrations via both pull (value unlock) and push (faster execution) mechanismsDatometry acquisition enabling faster, cheaper migrations from legacy systemsNo unusual margin headwinds in Q4; guided margin lower due to normal seasonal patterns

Raimo Linschau · Barclays

Asked Sridhar how zero-copy data sharing (promoted by vendors for ecosystem collaboration) will impact Snowflake in terms of adoption and monetization, given competitive pressure from SaaS vendors pushing back on data movement costs.

Sridhar characterized zero-copy as win-win enabling smoother data collaboration between SaaS vendors and Snowflake. Company has agreements with ServiceNow, Salesforce, SAP, and Workday. Reinforces Snowflake's position as centralized 'single pane of glass' for enterprise data. Zero-copy doesn't threaten monetization; rather, agentic AI makes aggregated data more valuable. Data source opacity is benefit to customers.

Zero-copy agreements with ServiceNow, Salesforce, SAP, WorkdayZero-copy enables SaaS vendors to efficiently share data without moving itSnowflake remains centralized repository for unified customer viewAgentic AI makes data location irrelevant to customers

Answers to last quarter's watch list

Whether Q3 product revenue beats the $1.125–1.130B guide by a comparable margin to Q2's ~$50M beat — Product revenue printed $1.158B, a ~$28M beat vs. high end. That's smaller than Q2's ~$50M beat, suggesting the consumption acceleration moderated. The beat is still meaningful but the magnitude has compressed.
Continue monitoring
NRR direction — Held at 125% for the third straight quarter. Neither broke above 127% (bull case) nor slipped to 123–124% (bear case). The metric remains the single unresolved tension in the print.
Continue monitoring
Sales productivity flow-through — RPO grew 37% YoY (vs. 33% in Q2 and 29% product revenue growth), and the company posted a record 615 new customer adds, suggesting the H1 S&M hiring is translating into both bookings and logos. The growth gap between RPO and product revenue widened, which is the right directional signal.
Resolved positively
Quantified AI revenue disclosure — Resolved this quarter. Sridhar disclosed a $100M AI revenue run rate, hit one quarter ahead of schedule, alongside the 50% AI-influenced bookings and 28% AI-incorporated use case figures. The bull/bear debate now has a real anchor number.
Resolved positively
Snowflake Postgres ramp — Not called out specifically on this print; no incremental customer or revenue disclosure. The company didn't update the Postgres adoption arc.
Continue monitoring

What to watch into next quarter

Whether Q4 product revenue beats $1.195–1.200B by at least ~$25M — Q3's beat magnitude of $28M is now the reference point. A sub-$20M beat would mark a clear moderation; a $40M+ beat would re-establish the "beat plus more" cadence.

Whether the Q4 operating margin guide of 7% holds or surprises higher — if Q4 prints closer to Q3's 11%, the FY guide reaffirmation at 9% was sandbag and operating leverage is intact. If Q4 hits 7% as guided, the Anthropic commitment and AI investment cycle are real margin headwinds that bears can underwrite.

AI revenue run rate progression beyond $100M — having disclosed the milestone, management has set up a quarterly expectation. The trajectory of the next disclosure (or the absence of one) will define the AI narrative through FY27.

NRR break in either direction — three consecutive quarters at 125% is now a flat trend, not a hold. Q4 needs to resolve whether AI is genuinely incremental spend (drives NRR above 127%) or whether it's reallocating existing budget (NRR drifts lower).

FY27 initial framing on the Q4 call — Snowflake typically frames the next year on the Q4 print. With AI revenue now quantified and the Anthropic commitment in place, FY27 product revenue growth guidance and operating margin trajectory will set the multi-year story.

Sources

  1. Snowflake Q3 FY2026 Press Release & Financial Statements — https://www.sec.gov/Archives/edgar/data/1640147/000164014725000207/fy2026q3earnings.htm
  2. Snowflake Q3 FY2026 earnings call Q&A (Sridhar Ramaswamy, Brian Robbins)

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