Snowflake Stock: AI‑Fueled Growth, Lofty Valuation And Analyst Upgrades Before Q3 FY26 Earnings

As the calendar flips to December 1, 2025, Snowflake Inc. (NYSE: SNOW) heads into one of its most closely watched earnings weeks yet. The AI Data Cloud company will report results for its fiscal third quarter of 2026 (covering the period ended October 31) after the market close on December 3, 2025. ^[1]

Shares are trading around the $250 mark after a powerful rebound in November and a year in which Snowflake has outpaced the S&P 500, the Nasdaq‑100 – and even Nvidia – with gains in roughly the high‑40% to low‑60% range year‑to‑date, depending on the data provider. ^[2]

At the same time, Wall Street keeps ratcheting up its expectations. Consensus forecasts call for another quarter of strong revenue and profit growth, analysts are lifting price targets, and Snowflake’s expanding AI toolkit – from its Cortex platform to new “agentic AI” features and a deepening partnership with NVIDIA – is reshaping the story investors are telling about the stock. ^[3]

But with a price‑to‑sales multiple near 19, persistent GAAP losses, and a stock that many commentators describe as “overvalued” and “not for the faint of heart,” Snowflake is also one of the most hotly debated AI winners on the market. ^[4]

Here’s what investors need to know heading into the December 3 earnings report – and how the latest AI deals, valuation arguments and analyst calls fit together as of December 1, 2025.

Snowflake Stock Is Outrunning The Market Into December

Across several independent sources, Snowflake’s share price performance in 2025 has been exceptional:

• A recent analysis notes the stock has surged about 48% year‑to‑date, beating the S&P 500, Nasdaq‑100 and even Nvidia. ^[5]
• TipRanks pegs the year‑to‑date rally at roughly 61%, driven by “continued product momentum due to the AI boom” and repeated earnings beats. ^[6]
• Over the last 12 months, StockAnalysis estimates the stock is up more than 45% and still about 11% below its 52‑week high near $281, with a 52‑week low around $120. ^[7]

On December 1, MarketBeat reports that SNOW opened around $251, giving the company a market cap in the mid‑$80 billion range. The article also highlights a 52‑week range of roughly $120–$281, a negative GAAP P/E ratio near ‑60, and institutional ownership above 65% of shares outstanding. ^[8]

Technically, Snowflake has been trading close to its 50‑day and 200‑day moving averages, reflecting a consolidation after a big run rather than a deep pullback. Investor’s Business Daily, in a recent earnings preview, described the stock as “in major growth mode” and “battling near its 10‑week moving average” while forming what could become a new base. ^[9]

Short‑term volatility remains elevated. A December forecast from 24/7 Wall St. notes that Snowflake shares fell about 5% over the past month after nearly 12% gains in the prior month, a pattern that underscores how quickly sentiment can swing around high‑multiple AI stories. ^[10]

In short: Snowflake goes into earnings priced for something special, not a ho‑hum quarter.

Earnings Preview: What Wall Street Expects On December 3

Street estimates: strong, but slowing growth

Across multiple research outlets, estimates for Snowflake’s Q3 FY26 look tightly clustered:

• EPS: Around $0.31, up roughly 55%–56% year‑over‑year. ^[11]
• Revenue: About $1.18 billion, implying 25%–26% growth versus the prior year. ^[12]

TipRanks notes that Wall Street expects Snowflake to continue its streak of beating expectations, and options markets are currently pricing an ~11% move in either direction on the earnings reaction, underscoring how binary this event could be for the stock in the near term. ^[13]

Recent performance: a reacceleration – and then a guidance reality check

Recent results set a high bar:

• In the second quarter of FY26, Snowflake reported product revenue around $1.09 billion, up about 32% year‑on‑year, an acceleration from roughly 26% growth in the prior quarter. ^[14]
• Investor’s Business Daily highlighted that total revenue was about $1.14 billion, and adjusted profit jumped 94% year‑over‑year, prompting a 20% one‑day surge in the stock back in August. ^[15]

However, guidance has already telegraphed some deceleration:

• Management pointed investors to Q3 product revenue of roughly $1.13 billion, implying around 26% growth, slower than the 32% pace seen in Q2. ^[16]

That gap – between accelerating recent results and more modest near‑term guidance – is central to how the Street will judge this upcoming report.

Under the hood: customers, RPO and net retention

Snowflake’s long‑term growth story is built on large enterprises consuming more services over time. The company’s investor relations site highlights several key metrics as of July 31, 2025 (Q2 FY26): ^[17]

• Remaining performance obligations (RPO):$6.9 billion
• Forbes Global 2000 customers:751
• Customers generating more than $1 million in trailing 12‑month product revenue:654
• Dollar‑based net revenue retention:125%

Investors will be watching whether:

• RPO continues to grow faster than current revenue (a sign of strong future demand), and
• Net revenue retention remains comfortably above 120%, signalling that existing customers are still expanding their usage of the AI Data Cloud.

Wall Street Is Turning Even More Bullish – With Caveats

Fresh target hikes on December 1

The first trading day of December brought another wave of bullishness.

Early on December 1, 2025, Rosenblatt Securities raised its Snowflake price target from $250 to $275 while reiterating a Buy rating. The new target assumes upside from roughly $251 per share and comes just two days before Q3 results. ^[18]

In its note, Rosenblatt:

• Nudged its organic product revenue growth estimate for Q3 to ~27% year‑over‑year, down from 32% in Q2 but still robust.
• Cited strong cloud service provider trends, positive checks from customer events, and ongoing healthy cloud migration as tailwinds.
• Highlighted that more than 4,000 customers were using Snowflake’s AI and machine‑learning technology weekly in Q2, underlining how central AI workloads have become to the platform. ^[19]

The Rosenblatt call follows a broader trend of target hikes:

• TipRanks notes that Oppenheimer recently lifted its target to $295 and keeps Snowflake as a “top pick”, expecting revenue growth potentially closer to 29–30%, above the current consensus. ^[20]
• MarketBeat’s institutional recap lists Barclays, Truist, JPMorgan and Canaccord all raising targets into the $255–$270 range since late August. ^[21]

Other aggregators paint a similar picture:

• Tickernerd cites a median 12‑month price target of about $274, with a high estimate of $500 and a low near $170, across 57 Wall Street analysts. ^[22]
• A separate Yahoo‑linked summary says the consensus target has recently ticked up from roughly $267 to about $273, reflecting “renewed optimism” among analysts. ^[23]

Depending on the dataset, these averages imply roughly 9–12% upside from current levels – healthy, but not explosive, given how fast the stock has already run.

Ratings remain positive, but not unanimous

• TipRanks shows a Strong Buy consensus based on 33 Buy and 3 Hold ratings, with an average target around $277. ^[24]
• MarketBeat’s compilation is slightly more cautious, with 2 Strong Buys, 34 Buys, 3 Holds and 3 Sells, resulting in an overall “Moderate Buy” and a consensus target near $268. ^[25]
• Tickernerd’s roll‑up indicates roughly 43 Buys, 6 Holds and 2 Sells across its coverage universe. ^[26]

In other words, most of Wall Street is bullish, but a non‑trivial minority worries the stock has already baked in much of the AI upside.

AI Is Now The Core Growth Engine

A big portion of the bullish thesis revolves around how deeply Snowflake is embedding AI into its core platform – and how much those capabilities can boost customer spend over time.

Cortex AI and AISQL: turning the Data Cloud into an AI factory

Snowflake’s Cortex AI offering makes a wide range of AI capabilities available as SQL and Python functions directly inside the platform, powered by leading large language models from OpenAI, Anthropic, Meta, Mistral and DeepSeek, as well as Snowflake’s own Arctic model. ^[27]

Documentation shows Cortex providing task‑specific functions such as: ^[28]

• AI_COMPLETE for general text and image generation
• AI_CLASSIFY and AI_FILTER for content classification and moderation
• AI_EMBED and AI_SIMILARITY for vector search and recommendations
• AI_EXTRACT and AI_PARSE_DOCUMENT for turning messy documents into structured data
• AI_SENTIMENT and AI_TRANSLATE for customer analytics and localization

Crucially, these models are hosted entirely within Snowflake, so the data never leaves the AI Data Cloud, which is a major selling point for heavily regulated industries.

Snowflake has also started to reimagine SQL itself for the AI era. In November, a research paper on Cortex AISQL described a production engine that blends traditional relational queries with semantic (LLM‑driven) operations. To handle the cost and latency of AI in production, AISQL introduces: ^[29]

• AI‑aware query optimization, which treats LLM inference cost as a first‑class concern and can yield 2–8x speed‑ups
• Adaptive model cascades, routing most rows through a cheaper model while escalating only tricky cases to a larger “oracle” model, achieving 2–6x cost savings with similar quality
• Semantic join rewriting, turning expensive join patterns into multi‑label classification tasks that can improve performance by 15–70x in production workloads

The message to customers: you can query both structured and unstructured data, with AI in the loop, using the same Snowflake environment you already know.

Enterprise AI use is exploding

Several recent reports reinforce that AI workloads are no longer a side project inside Snowflake:

• NAI500 notes that the number of customers using at least one of Snowflake’s AI products on a weekly basis jumped to 6,100 in Q2 FY26, more than doubling from about 2,500 a year earlier. ^[30]
• Rosenblatt’s note cites a slightly different datapoint – more than 4,000 weekly AI/ML customers – but the direction is the same: AI usage is scaling quickly across Snowflake’s installed base. ^[31]

That usage is being fueled by a steady drumbeat of AI‑centric product launches and partnerships over the last several weeks:

• NVIDIA CUDA‑X integration: Snowflake recently announced that Snowflake ML will ship with NVIDIA’s CUDA‑X data‑science libraries (cuDF, cuML, etc.) preinstalled, enabling GPU‑accelerated machine‑learning pipelines “with no code changes” for popular Python frameworks. NVIDIA’s benchmarks suggest certain workflows can run up to 200x faster on NVIDIA GPUs compared with CPUs. ^[32]
• SAP Business Data Cloud partnership: A new SAP Snowflake solution extension will make Snowflake’s AI Data Cloud directly available to SAP Business Data Cloud customers, with zero‑copy data sharing between the two platforms. The goal: unify semantically rich SAP data with Snowflake’s AI and analytics tools, allowing enterprises like AstraZeneca to build AI applications on top of real‑time operational data. ^[33]
• Agentic AI and “Snowflake Intelligence”: BusinessWire announcements referenced by Snowflake and aggregators describe Snowflake Intelligence as an enterprise intelligence agent that lets any business user ask complex questions in natural language and receive trustworthy answers drawn from governed data in Snowflake. It’s part of a broader push into agentic AI, with new developer tools and an “enterprise lakehouse” architecture meant to make it easier to build and deploy production‑grade AI agents. ^[34]

Put together, these initiatives support the core thesis behind Seeking Alpha’s “Stealthy Titan Ready For Explosive Growth In The AI Era” label: AI is quickly becoming Snowflake’s largest growth driver, layered on top of its legacy data‑warehousing and data‑sharing workloads. ^[35]

The Bear Case: Rich Valuation And Persistent GAAP Losses

While the AI story is powerful, the financials and valuation keep many investors on edge.

Growth is strong – but not cheap

NAI500’s deep dive into Snowflake’s recent numbers highlights the tension clearly: ^[36]

• Product revenue: About $1.09 billion in Q2 FY26, up 32% year‑on‑year.
• Guided product revenue: Around $1.13 billion for Q3, implying 26% growth and a step down from the Q2 acceleration.
• GAAP net loss: Nearly $298 million in Q2, and roughly $728 million for the first half of FY26.
• Adjusted profit: About $128.9 million in Q2, more than double the prior year, but heavily influenced by add‑backs like stock‑based compensation.
• Valuation: A price‑to‑sales ratio around 18.9, materially above many large cloud peers, even though Snowflake’s growth no longer meaningfully outpaces some of them.

Commentary around the Stealthy Titan article and related coverage is blunt: investors generally view the stock as overvalued, cite ongoing GAAP losses and warn of high execution risk. ^[37]

Other bearish or cautious pieces on platforms like Seeking Alpha hammer two recurring points (summarised by aggregators, not direct quotes): ^[38]

1. Non‑GAAP metrics can be misleading when stock‑based compensation is large, raising questions about the “true” profitability of the business.
2. Even if free cash flow improves, a valuation that looks “one step ahead” of fundamentals leaves little margin for error if growth slows.

Why some investors are trimming

On December 1, MarketBeat reported that Spyglass Capital Management reduced its Snowflake position by about 10% in the second quarter, though the stock still represents 6.4% of the firm’s portfolio and remains its third‑largest holding. Other institutional investors have added to positions, and in aggregate about 65% of Snowflake’s shares are held by institutions. ^[39]

Insider selling has also picked up, with directors and executives unloading more than 200,000 shares over the last quarter according to the same report – not unusual after a big run, but another data point for valuation‑sensitive investors to consider. ^[40]

The message from many cautious articles is not “Snowflake is doomed,” but rather: the story might be fantastic – the price already reflects it.

How The Valuation Debate Meets The AI Narrative

Putting the bull and bear cases together:

The bull view

Supporters of Snowflake tend to emphasize:

• Strategic position as the “AI operating layer” for enterprise data, unifying fragmented information across AWS, Azure and Google Cloud, which is a prerequisite for serious AI adoption. ^[41]
• Rapid growth in AI usage, with thousands of customers running weekly AI workloads on the platform and a fast‑expanding menu of AI services (Cortex functions, AISQL, agentic AI tools). ^[42]
• Major partnerships with NVIDIA, SAP and other ecosystem players, which deepen moats and help Snowflake tap massive installed bases like SAP’s enterprise customer universe. ^[43]
• Strong structural metrics like $6.9 billion of RPO, 125% net revenue retention, and hundreds of large‑spend customers, which suggest a long runway even if growth moderates. ^[44]

From this perspective, Snowflake is a leveraged play on the entire enterprise AI cycle – not just another SaaS company.

The bear view

Skeptics argue that:

• A near‑19x sales multiple is hard to justify for a company guiding to mid‑20s revenue growth, especially when hyperscalers like AWS and Google Cloud are building competing AI and data‑warehouse services. ^[45]
• The business remains GAAP‑unprofitable with large stock‑based compensation, which means shareholders are still heavily diluted to fund growth. ^[46]
• AI could become less proprietary over time, as open‑source models and rival data platforms mature, eroding Snowflake’s pricing power and differentiation. ^[47]

A widely held sentiment in more cautious coverage is that Snowflake is indeed a “stock of the future”, but perhaps one that requires a better entry point than the market currently offers heading into this earnings print. ^[48]

Five Questions Investors Should Ask On The Q3 FY26 Call

For investors trying to cut through the noise on December 3, five themes are likely to matter most:

1. How fast is AI monetizing?
   Management has shared usage stats for AI features; what investors really want to hear is how much revenue AI workloads are now contributing, how fast that slice is growing, and whether AI‑driven spend is offsetting any macro‑related optimization in traditional data‑warehouse usage. ^[49]
2. Is the growth deceleration a blip or a trend?
   The step down from 32% to mid‑20s percent product revenue growth is already in guidance. Any commentary that suggests growth can reaccelerate – or at least stabilize at the high‑20s – will be scrutinized, especially given recent analyst optimism that consensus is beatable. ^[50]
3. What’s the roadmap for GAAP profitability?
   With GAAP losses still sizeable, many investors will push for clearer timelines on operating margin expansion, stock‑based compensation discipline and eventual GAAP break‑even, not just improvements in adjusted metrics or free cash flow. ^[51]
4. How defensible is Snowflake’s AI moat against hyperscalers and Databricks?
   Snowflake’s partnerships with NVIDIA and SAP, its agentic‑AI push and its cross‑cloud capabilities are powerful, but AWS, Azure, Google Cloud and Databricks are not standing still. Any color on competitive win‑rates, migration activity and how open data formats affect Snowflake’s advantage will matter. ^[52]
5. How are large customers behaving?
   With 654 $1M+ customers, 751 Global 2000 accounts and billions in RPO, even small changes in big‑customer behavior can swing growth. Investors will want updates on expansion rates among top accounts, churn levels and the mix of new‑logo versus expansion‑driven revenue. ^[53]

Bottom Line For December 1, 2025

As of December 1, 2025, Snowflake sits at a fascinating crossroads:

• The company is deeply entwined with the AI boom, offering enterprises a unified data layer plus powerful AI primitives (Cortex, AISQL, agentic AI) and major ecosystem partnerships (NVIDIA, SAP). ^[54]
• Its operational performance is strong, with mid‑30s product growth in recent quarters, rising adjusted profits and best‑in‑class net retention and large‑customer metrics. ^[55]
• Yet the stock trades at a premium valuation, remains GAAP‑unprofitable, and has already delivered market‑crushing returns this year, leaving it vulnerable to any disappointment in guidance or AI monetization details. ^[56]

For growth‑oriented, AI‑focused investors with a high risk tolerance, Snowflake still looks like one of the clearest pure‑play ways to bet on the long‑term rise of enterprise AI and data‑driven applications.

For more valuation‑sensitive investors, however, the December 3 earnings call may be less about chasing the current rally and more about waiting to see whether fundamentals can grow into the price – or whether a post‑earnings pullback offers a more compelling entry point.

Either way, the next few days will go a long way toward determining whether Snowflake’s “stealthy titan” narrative is just beginning – or already priced to perfection.

This article is for informational purposes only and does not constitute financial advice or a recommendation to buy or sell any security. Always do your own research or consult a licensed financial advisor before making investment decisions.

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