At 5:00 a.m. Beijing time on February 26, Nvidia will release its fiscal year 2026 fourth-quarter earnings report.
This is not merely a chip company’s earnings disclosure. In 2026,
Nvidia has become one of the world’s most valuable companies, with its stock priced at $192.21 and a market capitalization reaching $4.67 trillion. Its earnings performance is widely regarded as a barometer for the global AI industry.
But what worries Wall Street is not just Nvidia’s own share price. Analysts broadly expect Nvidia to deliver results above expectations—HSBC Research forecasts quarterly revenue of $68 billion, about 3% above market consensus. The issue is that when markets grow accustomed to positive surprises, the marginal impact of those surprises diminishes. More importantly, the ripple effects of Nvidia’s earnings may extend much farther than most anticipate.
I. From Chips to Tokens: A Hidden Transmission Chain
How do Nvidia’s results influence the cryptocurrency market? The answer lies in four words: macro sentiment.
In 2026, the correlation between traditional tech stocks and cryptocurrencies has significantly strengthened. Data shows that during earnings season, Nvidia’s stock movements can explain 40% to 60% of the short-term variance in AI-related crypto assets, with correlation coefficients frequently ranging between 0.6 and 0.85. This means that every movement in Nvidia’s share price echoes somewhere in the crypto market.
The transmission mechanism is not complicated. When Nvidia delivers better-than-expected earnings and raises guidance, the market interprets this as a signal of strong demand for AI infrastructure. Optimism quickly spreads across risk assets, and as “high-beta assets,” cryptocurrencies often amplify gains by two to five times. Conversely, if earnings disappoint or guidance turns cautious, capital tends to flow out of high-risk assets and back into stablecoins or major tokens.
The impact goes beyond overall sentiment; it affects specific narrative sectors. AI-themed tokens such as Render (RNDR), linked to decentralized GPU networks; Fetch.ai (FET) and Bittensor (TAO), associated with inference markets; and The Graph (GRT), related to data indexing, often exhibit heightened volatility sensitivity around Nvidia’s earnings releases.
II. A Warning from the Software Sell-Off: Questioning the Sustainability of AI Spending
However, this earnings report comes against a more complex backdrop than before.
At the start of 2026, Wall Street witnessed a rare collapse in the software sector. The S&P 500 Software & Services Index fell more than 18% within just a few weeks, wiping out nearly $1 trillion in market value. This was not a cyclical correction but a deeper structural anxiety—markets began questioning whether AI Agents are fundamentally rewriting the value distribution logic of the software industry.
Previously, companies generated stable revenue through subscription models. But AI Agents can bypass traditional interfaces, directly understand user intent, and autonomously call APIs across multiple software systems. When Agents become the true entry point, standalone software products are reduced to “underlying capability modules,” significantly weakening software companies’ pricing power.
Why does this matter for Nvidia? Because the investment logic behind AI infrastructure is built on a core assumption: the application layer will continue expanding, driving demand for computing power. Cloud giants have sharply increased AI capital expenditures in recent years, with some companies reporting CapEx growth exceeding 50% year-over-year, betting on explosive AI application growth and rising compute rental demand.
But amid collapsing software valuations, markets are asking: when will these investments be monetized? If the application layer cannot generate sufficient profits to offset high token costs, cloud providers’ demand for computing power rentals may slow. This is a classic “bullwhip effect”: minor fluctuations in end-user demand become amplified into significant order volatility for upstream chip manufacturers.
III. Signals of Hardware Diversification: OpenAI’s “De-Nvidia” Move
At the hardware level, another signal is emerging.
Recently, OpenAI officially released the GPT-5.3-Codex-Spark model based on Cerebras wafer-scale chips. This marks the first substantive move by a leading mainstream model company to reduce reliance on Nvidia’s GPU ecosystem.
Although Nvidia still holds overwhelming market share in the short term and the CUDA ecosystem’s inertia remains strong with high migration costs, the symbolic significance of this shift cannot be ignored. When leading model companies begin exploring diversified chip solutions, the message is clear: no company wants to be locked into a single supplier. As one of Nvidia’s largest customers, OpenAI’s pivot toward Cerebras reflects not only cost or performance considerations but also strategic balance.
This does not mean Nvidia’s orders will immediately decline, but the capital market’s valuation premium for its “irreplaceability” may loosen. In the past, investors were willing to grant Nvidia a higher price-to-earnings multiple because they believed it was the only option. Now, if a second option exists, Nvidia’s pricing power faces constraints.
More importantly, if profitability at the application layer comes under pressure, customers will demand stricter returns on computing investments. At that point, issues of price, efficiency, and substitutability will regain prominence. Cloud providers may increasingly adopt in-house chips or third-party alternatives to lower procurement costs.
IV. Two Scenarios, Two Possibilities
Returning to Nvidia’s earnings itself, the market faces two potential scenarios.
Scenario One: Beat Expectations + Optimistic Guidance.
If Nvidia delivers stronger-than-expected results and Jensen Huang offers upbeat forward guidance during the earnings call—highlighting strong demand for next-generation chips such as Blackwell and Rubin and reiterating that the AI adoption cycle remains in its early stages—optimism will likely spill over quickly. AI-themed tokens could rise 10% to 30% over the following days or weeks, significantly outperforming the broader crypto market. Risk appetite would lift the entire crypto asset class, with capital potentially rotating from stablecoins into major tokens and sector leaders.
Scenario Two: In-Line Results + Cautious Guidance.
If performance merely meets expectations or management adopts a cautious tone—citing margin pressures from rising memory chip prices, intensifying competition, or uncertainty in customer capital expenditure timing—the market may reassess the pace of AI infrastructure investment. AI tokens often experience mean-reversion sell-offs in such cases. Capital may flow out of higher-risk assets, while Bitcoin and Ethereum could see their relative value as defensive core holdings highlighted.
It is worth noting that in three of the past four quarters, despite Nvidia exceeding earnings expectations, its stock price fell the day after the release. Whether this “sell-the-news” dynamic will transmit to the crypto market is something investors should watch closely.
V. Investors Positioned Along the Transmission Chain
For crypto asset holders, Nvidia’s earnings are no longer an external event that can be ignored.
If you hold AI-sector tokens, focus not only on the headline numbers but also on key signals from the earnings call: Is data center revenue continuing to grow? Are comments on cloud capital expenditures positive? What is the margin trend? What are the production capacity and demand expectations for next-generation chips? These details will directly shape the strength of the AI narrative in the coming quarter.
If your portfolio is primarily Bitcoin and Ethereum, the impact of Nvidia’s earnings may be more indirect but remains significant. As an amplifier of macro sentiment, Nvidia’s performance influences overall risk appetite and capital flows. An optimistic report may push funds from stablecoins into major tokens; a pessimistic one could reinforce risk-off sentiment and prompt temporary capital retreat.
Options pricing suggests traders expect Nvidia’s stock to move by as much as 6% this week. Given that Nvidia accounts for roughly 8% of the S&P 500’s weighting, such volatility alone could have broad market implications. When the largest tech stock starts to sway, no risk asset remains untouched.
Conclusion
At 5:00 a.m. Beijing time on February 26, Nvidia’s earnings will be unveiled on schedule.
Regardless of the outcome, one thing is certain: this is no longer just a chip company’s earnings report. In 2026, as AI becomes the core narrative of the global economy and the linkage between tech stocks and cryptocurrencies tightens, each Nvidia earnings release serves as a stress test for confidence in the AI industry.
The results will travel from Nasdaq to Binance, from Wall Street to crypto communities. Investors positioned along the transmission chain need not predict direction, but they must understand the pathways of transmission—and know where they stand when volatility arrives.