To The Moon

Alphabet announced the launch of Gemini 3 Pro, this will take the AI race to a new level, so can this new launch propel Google to become the new King of the Year?

Given the launch of Gemini 3 Pro by $Alphabet(GOOGL)$ and the response from OpenAI with GPT‑5.1. In this article I would like to discuss and share how that plays into positions in GOOGL, $Microsoft(MSFT)$ and $NVIDIA(NVDA)$.

What’s Going On

Gemini 3 Pro (Alphabet):

Alphabet announced Gemini 3 Pro (and “Deep Think” mode) as their next-gen AI model, with strong claims of state-of-the-art performance in reasoning, multimodality (text+image+video+audio+code) and large context windows.

The rollout is in Google products (Search, YouTube, Android, Workspace) — meaning it has potential for massive scale, leveraging Alphabet’s existing ecosystem.

Press commentary sees this as a “structural AI winner” candidate for Alphabet.

GPT-5.1 (OpenAI):

OpenAI’s latest model, GPT-5.1, introduces two variants: “Instant” (fast conversational) and “Thinking” (deeper reasoning) plus improved tone, tool-use, and coding performance.

Also tied into Microsoft via the partnership (MSFT’s Copilot studio uses GPT-5.1) so it reinforces / extends Microsoft’s AI platform play.

The wider backdrop:

The AI “arms race” among the tech giants is very much in motion: models → infrastructure → distribution → monetization.

Infrastructure players (chips, datacenters) are critical. So NVDA (as the leading GPU & AI-infrastructure play) remains highly relevant.

How This Could Play Out — “King of the Year?” & Competitive Dynamics

Will Alphabet become “King of the Year”?

Pros: Alphabet has scale, massive user base, and synergy across Search/YouTube/Android/Cloud. Gemini 3 gives them a plausible seasonal leap in AI capability and differentiation.

Risks: Execution matters — it’s one thing to announce the model, another to monetize meaningfully, integrate across products, fend off privacy/regulation issues, and maintain differentiation.

I would think so — there is a genuine upside case that Alphabet could be the standout for 2026 (if the rollout is strong). But “king” status is far from assured.

Will OpenAI/Microsoft Give Them A Run For Their Money?

Absolutely. OpenAI with GPT-5.1 already has a model in market (or rolling out) and Microsoft is deeply tied in. So Microsoft’s AI + cloud + enterprise distribution is a serious competitor.

The advantage for Microsoft: enterprise adoption, hybrid cloud + AI, strong sales channel.

For OpenAI: model innovation and developer ecosystem.

NVIDIA’s Role (“winning at the sideline”):

NVIDIA plays as the foundational infrastructure supplier (GPUs, DGX pods, etc.). Even if they aren’t “the chatbot company”, every major AI model still needs the hardware stack.

So NVDA has a potential “earnings multiple leverage” to AI model demand irrespective of who the model winner is.

Investor Positioning: GOOGL, MSFT, NVDA — What To Consider And How To Weight

Here’s how I would think about it (not personal advice, just framework):

Our “Recommendation” Tilt (if one scenario were to be picked)

Given the above, if we were choosing a tilt today:

We would overweight NVDA slightly because the infrastructure lever is clear and the risk of being “wrong model winner” is mitigated (everyone needs chips).

We would have a meaningful position in GOOGL as the potential “platform winner” in AI, if comfortable with some execution & regulatory risk.

We would keep MSFT in the portfolio as a “safer but lower upside” anchor — maybe maintain or slightly overweight depending on current weighting.

If one has limited capital and only one pick: perhaps NVDA (infrastructure) + GOOGL (platform) as twin bets (one indirect/infrastructure, one direct/model/scale). MSFT as “nice to have.”

Things To Watch / Risks To Monitor

Model rollout effectiveness: Will Gemini 3 Pro actually deliver meaningful usage growth + monetization for Alphabet?

Competitive surprises: Could another player (e.g., Anthropic, Amazon Web Services) disrupt the narrative?

Regulation & privacy: Especially for Alphabet and Microsoft (data usage, AI safety, antitrust risk).

Infrastructure constraints / China competition: For NVIDIA, supply chain or geopolitical issues could hit.

Valuation: Huge expectations are priced in. If growth is delayed, the risk of “buy the rumor, sell the fact” is real.

Final thought

Yes: Alphabet has real potential to “be the king” in 2026 if Gemini 3 Pro rollout goes well, but this is high risk/high reward.

Microsoft and OpenAI are not just “also-rans” — they are strong adversaries and may well split the winner’s circle (so a duopoly rather than single king).

NVIDIA is the infrastructure play that might win regardless of which AI “model company” wins — and thus offers a slightly more de-risked way to play the AI surge.

In the next section, I would like to look at some valuation metrics (forward P/E, AI-related growth, cloud growth) for GOOGL / MSFT / NVDA and show what kind of “upside scenarios” might look like (and what the risk-downside looks like).

Here is a more detailed valuation-and-scenario analysis for GOOGL, MSFT, and NVDA, incorporating forward P/E, cloud/AI growth, and risk-upside cases. (Note: these are frameworks + scenario estimates, not predictions.)

Key Valuation Metrics & Growth Drivers

Here is a breakdown of key metrics for each company, plus potential upside/downside scenarios based on AI + cloud growth.

1. Alphabet (GOOGL)

Valuation & Metrics

According to analysis, GOOGL’s forward P/E is in the ~24–26x range.

According to one deep-dive: P/E (trailing) ~27.3x; forward P/E estimate ~25.8–28.9x.

PEG ratio (5-yr growth implied) has been cited around ~1.6–1.7.

P/S ratio is quite high: estimated trailing P/S ~8x per some analyses.

Growth Drivers

Cloud (GCP): Very strong momentum: some reports say Google Cloud revenue grew ~32% YoY to US$13.6B in one quarter.

Cloud backlog: According to Seeking Alpha research, Google’s cloud backlog is ~US$106 B, which offers visibility.

CapEx: Alphabet is guiding very high CapEx for AI and cloud infrastructure; some sources say ~$85B in 2025 will go into servers/data centers/chips.

Margins: As cloud scales and they deploy TPUs and efficient infrastructure, operating margins could improve long term.

Advertising + AI monetization: While ad remains core, more of Google’s future value may come from AI-powered products + cloud + “Other Bets.”

Upside Scenarios

Here are a few potential scenarios for GOOGL, depending on how well its AI + cloud strategy executes:

Risks to Watch

Heavy capital spending risk: $85B+ CapEx is very large, and if cloud/AI monetization doesn’t scale, ROI could be weak.

Competition: Azure, AWS, other AI/cloud providers are strong.

Regulatory risk: Google’s core ad business is always exposed.

Execution uncertainty: Building data centers is one thing; turning that into high-margin recurring AI / cloud revenue is a different challenge.

2. Microsoft (MSFT)

Valuation & Metrics

MSFT’s current P/E (per the finance data) is about 36.7x, which suggests the market is pricing in continued high-growth.

According to some commentary, the forward P/E is ~37.7x.

Gross margin for Microsoft Cloud is pressured by AI infrastructure scaling: in FY25, cloud gross margin dropped (per their earnings) because of AI capex.

Growth Drivers

Azure Cloud Growth: In Q3 FY25, Azure + other cloud services grew 33% YoY, with 16 percentage points of that coming from AI services.

In Q4 FY25, per earnings commentary, Azure grew ~39%.

Backlog / Bookings: Some reports (EarningsIQ) suggest strong remaining performance obligations (RPO) → good visibility.

AI Integration: Microsoft is embedding AI deeply: AI-first data centers, custom chips for Azure, Copilot in Microsoft 365 / Dynamics / GitHub, etc.

CapEx: Continuing large CapEx to scale data centers for AI. (From Q4 commentary.)

Upside Scenarios

Risks to Watch

AI infrastructure costs could bite margins if not offset by price / usage.

Supply chain / capacity: even Microsoft is warning of AI capacity constraints. Microsoft

Competition: Other cloud + AI providers.

Execution risk in scaling and converting bookings into profitable AI revenue.

3. NVIDIA (NVDA)

Valuation & Metrics

While official forward P/E is not always public in these write-ups, there are consistent commentary indicating forward P/E in the high 20s (e.g., ~28–29×).

Based on recent deep-dive research: very high growth in data center / AI GPU business; huge operating leverage.

According to Katusa Research: very large upside potential driven by data center demand.

Growth Drivers

Data Center / AI GPU: This is NVDA’s core AI engine. According to Thunder Equity Research, data center is driving a huge part of NVDA’s revenue, with very strong growth.

High Margins: NVDA has very strong gross margins in its AI/data center business, giving it operating leverage.

Hyper-scale Demand: Many cloud providers, enterprise AI labs, and researchers will continue to need top-tier GPUs (or Blackwell / next-gen architecture).

R&D / Innovation: NVDA continues to push architecture, software stack (CUDA, etc.), and more efficient chips, which could extend its lead.

Upside Scenarios

Risks to Watch

Heavy reliance on capital expenditures from external customers; if hyperscaler capex slows, demand for NVidia GPUs may soften.

High concentration risk: some large customers contribute a big portion of data-center revenue.

Competition from other AI accelerators (custom chips, in-house designs from cloud providers).

Geopolitical risk (export restrictions), supply chain constraints.

Putting It Together: Scenario Analysis & Portfolio Implications

Here is how these valuation + growth dynamics might inform an investor positioning strategy, given your original question about who might “win”:

Balanced AI+Infrastructure Exposure:

Use NVDA as your infrastructure play. If AI demand remains robust, NVDA is likely to benefit even if model-providers shift or compete: everyone needs compute.

Use GOOGL as a platform + model play: strong cloud + potential for deep AI monetization (search + Gemini + enterprise).

Use MSFT as a more diversified play: cloud + enterprise + productivity + AI. It’s less “pure AI bet” than NVDA, but more defensible and broad.

Risk Management:

Because all three are exposed to AI risk, make sure your sizing reflects conviction + risk tolerance.

Monitor capex trends, earnings guidance, and bookings / backlog as leading indicators.

Be ready to trim if valuation multiples start to compress (especially for NVDA or MSFT), or if growth guidance weakens.

Time Horizon:

These are multi-year plays in many respects: the returns, especially from cloud and compute investment, may take years to fully materialize.

If you're more short-term (12–18 months), you may lean more into momentum (NVDA) but be aware of valuation vulnerability.

For long-term (3–5 years+), a blend (GOOGL + MSFT + NVDA) might be the most balanced way to capture platform, compute, and scale.

Our Current Lean (Given Gemini 3 Pro and GPT-5.1 Race)

GOOGL: I lean more bullish here — Gemini, strong cloud backlog, and capex commitment could pay off. If Google captures AI enterprise + consumer usage, its valuation could re-rate.

NVDA: Still very compelling as the infrastructure backbone of the AI boom — high conviction, but size position carefully because of multiple risk.

MSFT: A core “anchor” in the portfolio — less volatile than NVDA, deeply embedded in enterprise AI, but not as “levered” to pure compute as NVDA or model-play as GOOGL.

In the following section, we would walk through a simplified DCF-style forward valuation for GOOGL, MSFT, and NVDA, under different AI-growth assumptions. (Note: this is a modeling exercise, not a precise price prediction. Real-world valuation would depend on many more factors.)

DCF-Style Assumptions & Framework

Here are the key modeling assumptions common to all three:

Base Free Cash Flow (FCF) — we start from a recent FCF number.

Growth rates — we assume different FCF CAGRs over 3-year and 5-year horizons, based on AI/cloud demand scenarios.

Terminal growth rate — after the explicit forecast period, we assume a modest perpetual growth (“g”) for FCF.

Discount rate (WACC / required return) — we pick a reasonable discount rate for a large tech company; here assumed ~8% (you could argue for higher or lower).

Terminal multiple — or we compute terminal value via a Gordon Growth model.

Key Inputs (Per Company)

Here are the base inputs / anchor numbers I used, based on public data + proxy estimates:

Scenarios & Valuation

We model three scenarios for each company: Base, Bull, Bear, with different FCF growth assumptions.

Here are the assumptions:

Discount rate (WACC): 8%

Sensitivity & Key Take-Homes

Sensitivity to growth: These valuations are very sensitive to the assumed FCF growth rates. A few percentage points difference in CAGR or terminal growth makes a big difference in terminal value.

CapEx risk: For both GOOGL and MSFT, the AI capex is huge. If this spending doesn't convert into proportionally higher FCF, then downside risk is real.

Discount rate matters: If investors demand a higher return (say 9–10% instead of 8%), the implied valuations drop significantly.

Time horizon: These DCFs assume a 5-year explicit forecast + terminal value; the real AI payoff could be more long-dated, or could accelerate.

Conclusion & Implications for Positioning

GOOGL: Under the bull case (strong AI/cloud execution), there is material upside from the current price (model suggests potential for $400+ in very optimistic case), but near-term risk if capex or AI monetization disappoints is non-trivial.

MSFT: A solid long-term DCF case if AI + cloud demand continues, but high capex + margin risk could temper near-term FCF.

NVDA: Probably the most leveraged to “AI infrastructure wins.” In a bullish AI growth case, NVDA’s FCF could explode, giving very high terminal value. But if growth slows, downside is significant because the valuation is rich.

Summary

The AI landscape has shifted violently in November 2025. With Google’s Gemini 3 Pro (launched Nov 18) and OpenAI’s GPT-5.1 (launched Nov 12), the race has moved from "chatbots" to deep reasoning and ecosystem dominance.

Here is the summary and investment playbook for late 2025.

The Verdict: Gemini 3 Pro vs. GPT-5.1

Google (Gemini 3 Pro): The current momentum leader. Google didn’t just launch a model; it successfully deployed it across Search, Workspace, and Android immediately. Early benchmarks show it edging out GPT-5.1 in multimodal reasoning and coding. Crucially, Google has proved it can integrate AI without killing its ad business, removing the "existential threat" discount on the stock.

OpenAI (GPT-5.1 Thinking): A technical marvel but facing distribution friction. The "Thinking" model excels at complex logic ("System 2" thinking), but Microsoft’s Copilot integration feels clunkier compared to Google’s native seamlessness. OpenAI is fighting a war on two fronts: fighting Google for dominance and fighting to keep users off agnostic platforms.

Investment Positioning Strategy

Alphabet (GOOGL) – The "Comeback King" (Aggressive Buy)

• Thesis: Wall Street’s fear that "Search is dead" is evaporating. Gemini 3 Pro proves Google has the best data moat and distribution.

• Play: Overweight. The stock is breaking out as sentiment shifts from "fear of disruption" to "AI execution leader."

Nvidia (NVDA) – The Undisputed Winner (Core Holding)

• Thesis: It does not matter who wins the model war; both Gemini 3 and GPT-5.1 require exponentially more compute for their "reasoning" phases. Nvidia’s recent earnings confirm that demand for Blackwell chips is outstripping supply.

• Play: Buy/Hold. They are the "arms dealer" in an escalating war. Volatility is the price of admission for this growth.

Microsoft (MSFT) – The "Hedged" Giant (Accumulate)

• Thesis: Microsoft is in a complex spot. While Copilot is facing heat from Gemini, Microsoft is brilliantly hedging its bets. Recent reports indicate they are diversifying by deepening ties with Anthropic (alongside Nvidia), reducing their fatal reliance on OpenAI.

• Play: Long-term Hold. They own the enterprise workflow. Even if Google wins the consumer "search" war, Microsoft wins the corporate "work" war.

Technologically, Google has snatched the crown for late 2025 by solving the "intelligence vs. speed" trade-off. Financially, Nvidia remains the king, as every new model launch acts as a direct deposit into their revenue stream.

Appreciate if you could share your thoughts in the comment section whether you think Google would be in a good position to snatch the crown for late 2025?

@TigerStars @Daily_Discussion @Tiger_Earnings @TigerWire @MillionaireTiger appreciate if you could feature this article so that fellow tiger would benefit from my investing and trading thoughts.

Disclaimer: The analysis and result presented does not recommend or suggest any investing in the said stock. This is purely for Analysis.