To The Moon

$NVIDIA(NVDA)$ Q3 earnings have beaten expectations, and market have moved after hours trading. Are we going to see Nvidia earnings helping to push for a broader market sentiment and also performance until the end of 2025?

In this article, I would like to discuss on how we can NVIDIA Corp.’s (NVDA) strong Q3 earnings and what it might mean for broader market sentiment — and the rally potential for both chip/hardware stocks and AI software stocks through end-2025.

What The Nvidia Earnings Tell Us

The headline facts

Nvidia reported revenue of $57 billion in Q3 FY2026, beating consensus.

Data-centre segment (the core of its AI play) was very strong.

Nvidia guided Q4 revenue at about $65 billion, above expectations

The company framed its business as not just a short-term “AI hype” play, but as a longer-term structural demand story: “AI ecosystem is scaling fast.”

Why this matters for the wider market

Nvidia is seen as a bellwether for the AI infrastructure cycle: when it performs well, it suggests the hardware and systems side of generative AI are moving from hype to real deployment.

The positive surprise and strong outlook help ease concerns that the AI trade was purely speculative — investors needed proof-points.

Because Nvidia is large and influential (and part of key indices), its performance has the power to sway sentiment across tech, semiconductors and even the broader equity market.

But there are still caution flags

• Even with the strong beat, some analysts emphasise the risk of valuation stretchedness: high growth expectations baked into the stock.

• The guidance, while strong, will need to be validated by peers (for example semiconductor suppliers, memory/chip manufacturers) to sustain the bull case.

• Export restrictions, supply-chain constraints (e.g., China exposure) remain potential headwinds.

Implications for Market Sentiment until End of 2025

Given Nvidia’s results, what are the likely broader implications for market direction through year-end?

Positive tailwinds

A strong Nvidia print gives confidence that the growth in AI infrastructure is real and not just narrative. This could spur investor appetite for stocks in that ecosystem.

That may encourage risk-on sentiment — tech, growth, innovation sectors may get a boost as one of the core players delivers.

If other chips and AI-hardware companies post strong earnings (or at least guidance), the rally could broaden from the few megacaps into the wider tech/supply-chain base.

Risks/what will temper the enthusiasm

A lot of this is about expectations: high growth is already built‐in. So even a good result must exceed expectations significantly to keep the momentum.

If peers or suppliers show weaker performance, or guidance is anaemic, the positive sentiment may fade or reverse.

Macro issues (rates, inflation, recession risk) still loom: even for high-growth stocks, if the broader economy slows or rates stay high, that can dampen upside.

Valuation risk: if the market believes the premium for “AI growth” is too aggressive and the real results don’t match, there could be multiple compression.

Our View: Probable Scenario

We would expect that market sentiment will remain positive but selective: hardware/semiconductor names related to AI infrastructure get the near-term shine.

Through end-2025, I think we will see moderate rally potential, especially if macro tailwinds (rate cuts, economic data) align. It may not be an “everything goes up” scenario; rather the winners will be those with real proof of scalable AI-business and strong execution.

The upside could be fairly meaningful, but the risk of a pull-back is also there if any disappointments crop up.

Chip Stocks vs AI Software Stocks: Which Gets The Rally?

Which category is more likely to lead the next leg: hardware/chip makers or AI software/platform companies?

Chip / Hardware / Infrastructure plays

Pros:

They are direct beneficiaries of the surge in demand for AI models and data-centres: GPUs, accelerators, memory, infrastructure.

Nvidia’s results suggest the hardware side still has momentum and can support earnings growth.

The “proof” seems to be in the hardware spend, so the market may reward companies enabling that infrastructure.

Cons:

Hardware typically has longer lead times, capital intensity, margin risk, and can suffer from supply constraints or cycles.

If the AI build-out is already broadly expected, some hardware upside may be priced in already.

AI Software / Platform companies

Pros:

Software has higher margin potential, recurring revenue, scalability — from an investment standpoint attractive.

As AI models move from experimentation to deployment, software/AI services may capture significant value (applications, enterprise deployments, tools).

Once the underlying infrastructure is proven, the software layer tends to get more attention.

Cons:

Software companies often face competition, execution risk (making meaningful revenue from AI is complex).

Much of the hype for “AI software” is ahead of the value capture; thus valuations may be more stretched and the risk of disappointment higher.

These companies sometimes require more time to show tangible returns; the market may be less patient.

Our Balanced View

Near term (next few quarters): hardware/chip stocks may lead because the infrastructure build is already underway and earnings surprise potential is higher.

Medium term (into 2025 end and beyond): software/AI platform companies might take over as the story shifts from “build the infrastructure” to “deploy at scale and monetise”.

So ideally: first wave hardware/infrastructure → second wave software/applications.

Key Factors To Watch

To monitor how this plays out, here are what we would keep an eye on:

Earnings and guidance from major chip/semiconductor companies (memory, foundries, AI-chip suppliers). If they deliver, the infrastructure story strengthens.

Results and commercial updates from AI software/application companies: are they converting AI hype into real revenue?

Macro environment: interest rates (if cuts come, that’s favourable for high-growth tech), economic growth, corporate capex.

Valuation dynamics: are multiples expanding further or compressing? Are investors rewarding execution or just expectations?

Regulatory and geopolitical risks (especially around China export restrictions, AI governance).

Supply-chain issues: hardware shortage, manufacturing ramp-up delays, etc.

Nvidia’s strong earnings are a positive trigger for both market sentiment and the AI/hardware ecosystem. The likely path is a rally led first by chip/infrastructure names, followed by a broader move into AI software/application names — but with caution: high expectations, execution risk, and macro headwinds remain.

In the next section, we would like to share some specific companies in the chip (hardware) and AI-software spaces that look well-positioned for a potential AI-driven rally, along with key risks for each.

1. Advanced Micro Devices (AMD)

Why well-positioned:

• $Advanced Micro Devices(AMD)$ is pushing into the AI data-center market with its MI-series (AI accelerators) and EPYC CPUs.

• It has a “dual-play” — CPU + GPU — which gives it flexibility and potential to win in a broader set of AI compute workloads.

Risks:

• Intense competition from Nvidia, particularly on the GPU / high-performance AI accelerator side.

• Execution risk: delivering on future MI-series roadmap (or next-gen products) may require heavy R&D and capital.

• Margin pressure: AI accelerators may have different margin profiles than traditional product lines, depending on cost structure and volume.

2. Broadcom (AVGO)

Why well-positioned:

• $Broadcom(AVGO)$ is increasingly seen as a “quiet winner” in AI infrastructure: it offers custom AI accelerators (XPUs) and has strong networking capabilities.

• According to analyst commentary, Broadcom has won significant orders from hyperscalers, making it more than just a peripheral AI chip supplier.

• Its mix of semiconductor + infrastructure software gives it a diversified exposure to the AI build-out.

Risks:

• Customer concentration: AI chip demand may depend heavily on a few hyperscale customers; any slowdown or design changes could be impactful.

• Execution risk on custom chip projects (XPUs) — design wins don’t always guarantee volume or margin.

• Valuation: as more competition comes into the custom silicon / data center chip space, Broadcom may need to invest heavily to maintain growth.

3. Marvell Technology (MRVL)

Why well-positioned:

• Marvell Technology (MRVL) has made a big push into custom AI silicon (“XPU”) for data centers. Their custom-chip programs are reportedly scaling.

• According to management, a large portion of its data center/AI business comes from custom silicon and interconnect/optics.

• Forecasts from Marvell suggest that its AI chip sales could hit US$2.5 billion by its fiscal 2026, driven by both custom chips and optics.

Risks:

• Custom silicon is lumpy: because a few big cloud players (hyperscalers) drive these projects, revenue could be very “lumpy” between design wins and production.

• Margin risk: Marvell’s custom silicon tends to have lower margins than its merchant (off-the-shelf) products. Yahoo Tech

• Concentration: As its data center business grows, Marvell may be increasingly dependent on hyperscaler capex, exposing it to swings in cloud AI spending.

• Geopolitical / supply chain risk: As with many semis, tight coordination is needed, and any wafer / packaging / logistics disruption (or geopolitical tension) could hurt.

4. Taiwan Semiconductor Manufacturing Company (TSMC)

Why well-positioned:

• As the leading foundry, TSMC is crucial to virtually all major AI chip players (Nvidia, AMD, custom-silicon folks). This gives it “picks and shovels” exposure to the AI infrastructure build-out. The Motley Fool

• Its node roadmap (advanced process tech) is critical to cutting-edge AI chips; strong foundry partners are likely to continue investing.

Risks:

• Foundry risk: Capex is huge, and demand forecasting can be difficult — a drop in AI chip demand could lead to overcapacity.

• Geopolitical risk: TSMC’s manufacturing base (especially in Taiwan) carries geopolitical exposure.

• Competitive risk: Other foundries and in-house silicon from cloud players may erode TSMC’s dominance or margins in the long run.

5. Micron Technology (MU)

Why well-positioned:

• Memory is a critical part of AI infrastructure. High-bandwidth memory (HBM) is especially important for training and inference workloads.

• According to some reports, Micron is “completely sold out” of HBM3E (or very tight) for certain periods — suggesting strong demand.

Risks:

• Memory cycles are volatile: pricing for DRAM and HBM can swing, and inventory dynamics may bite.

• Capex intensity: Memory companies need to invest heavily in fabs, and if demand slows, that capex may not pay off.

• Competition from other memory suppliers; also, if AI hardware manufacturers optimize memory use, the growth could be less straightforward.

AI Software / Platform / Application Plays

On the software side, here are some companies (or types of companies) that could benefit from broader AI adoption:

1. LightOn (Europe)

• LightOn is a French AI company that offers an enterprise generative AI on-prem platform.

• Its “Paradigm” platform is targeted at enterprises wanting to run LLMs or generative AI workloads in their own environments (not fully in public cloud).

Risks:

• Being a smaller / more specialized AI software company, it may face scaling challenges.

• On-prem AI adoption is still somewhat niche compared to cloud: the TAM (total addressable market) might grow, but the adoption curve could be slower.

• Capital intensity / R&D risk: building enterprise-grade generative AI infrastructure is not cheap; sustained investment is needed.

• Competition: from both public cloud providers (who offer SaaS AI) and other enterprise AI vendors.

2. Phunware

• $Phunware, Inc.(PHUN)$ is a public company that has moved into generative AI, offering mobile-app platforms, digital engagement, and more.

• Their strengths lie in real-time user engagement, mobile experiences, and potentially “agentic” or conversational AI.

Risks:

• Very niche: its market may be limited compared to large cloud / enterprise AI software players.

• Execution risk: transforming from mobile software company to a meaningful AI platform company is nontrivial.

• Competition risk: many larger players (Microsoft, Google, AWS) dominate AI tooling and platform, and could compete aggressively.

3. OpenText

• OpenText is a long-established enterprise software company in content management, information management, analytics, etc.

• They could benefit from AI as enterprises increasingly embed generative AI / ML into content workflows, document processing, knowledge management.

Risks:

• Legacy business risk: part of its revenue comes from non-AI legacy product lines; transitioning fully to AI-enabled workflows may be slow.

• Competition: in the enterprise AI space, there are many strong SaaS players, and OpenText may not be the first choice for cutting-edge AI-first companies.

• Execution of AI strategy: success depends on how well OpenText can integrate generative AI into its product suite and monetize it.

Our Strategic Take

Putting together the thesis:

1. Infrastructure (Chips) plays like AMD, Broadcom, Marvell, $Taiwan Semiconductor Manufacturing(TSM)$, Micron are likely to capture the early waves of AI infrastructure spending (training, inference, custom silicon).

2. Software / Platform plays may take over later or in parallel as deployment of these AI models scales into enterprise use-cases; but many are riskier, especially smaller or legacy software firms.

3. A balanced exposure might make sense: some weight on infrastructure (for nearer-term earnings leverage) + selective software plays (for long-term optionality).

Summary

Nvidia’s Q3 earnings (reported November 19, 2025) serve as a critical "green light" for the market, effectively dispelling recent fears of an AI bubble. Here is the deciphered signal and outlook through year-end 2025.

Deciphering the Earnings

The Numbers: Nvidia delivered $57.0B in revenue (beating the $54.9B expectation) and $1.30 EPS. Most importantly, Q4 revenue guidance was raised to $65.0B, signaling accelerating growth rather than a slowdown.

The Signal: The "AI Infrastructure" trade is far from over. Demand for the new Blackwell chips is outstripping supply, and major tech giants (Hyperscalers) are increasing, not cutting, their capital expenditure. This confirms that the AI trend is structural, backed by real corporate spending, not just speculative hype.

Sector Outlook: Chips vs. Software

For the remainder of 2025, the market favors a Hardware-First Rally.

Chip Stocks (Immediate Winners): Nvidia’s guidance confirms that the "build-out" phase is still the primary driver. Expect a strong year-end rally for Nvidia (NVDA) and key supply chain partners like TSMC and HBM (memory) manufacturers. The "rising tide" of infrastructure spending lifts these boats first.

AI Software (The "Next" Trade): While software stocks may see sympathy gains, they are secondary for now. The focus remains on building the data centers. However, look for early leaders in "Agentic AI" (AI that performs tasks) to begin outperforming as the market looks toward 2026 for ROI stories.

Nvidia’s beat confirms the bull market is intact. Expect Chip stocks to lead the rally into 2026, while Software remains a "stock-picker's" market requiring proof of monetization.

Appreciate if you could share your thoughts in the comment section whether you think Nvidia would continue to lead the chip stocks into a 2026 rally.

@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.