The AI ​​Stock Bubble Threatens to Burst, Is Competition in the K3 Chemical Industry a New Trigger?

Concerns about an AI stock bubble have resurfaced after Kimi K3 intensified competition in the global artificial intelligence market. Peter Schiff believes that pressure from China’s AI sector could expose weaknesses in tech stock valuations, which have long been propped up by extremely high growth expectations.

Key Takeaways

• Kimi K3 adds competitive pressure by offering large-scale models for coding, reasoning, and agent-based work.
• Lower-cost AI competition could squeeze American companies' margins and test the scale of AI infrastructure spending.
• The AI ​​stock bubble cannot yet be declared definitively burst as many major companies are still generating strong revenue, profits, and cash flow.

What Is an AI Stock Bubble?

An AI stock bubble is a condition where the stock prices of companies related to artificial intelligence increase much faster than the ability of their businesses to generate revenue, profits, and cash flow.

Rising prices don't always indicate a bubble. The stock market does attempt to predict future profits. Investors may assign high valuations to companies with significant growth opportunities, superior technology, and strong market positions.

Sumber AI Generated Image

Problems arise when prices start to rely on overly optimistic assumptions, such as:

• Revenue growth will continue to increase without any obstacles.
• AI shopping always yields high profits.
• Market leaders will not face new competitors.
• The demand for chips and data centers will not slow down.
• AI business margins will remain large.
• Customers are willing to pay premium prices in the long term.
• All companies that use the AI ​​label will gain economic benefits.

A bubble forms when the narrative becomes more dominant than the fundamentals. Under these conditions, even minor news can trigger a sharp correction because stock prices have already anticipated a near-perfect scenario.

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Why Is Peter Schiff Warning About an AI Stock Bubble?

Peter Schiff believes the AI ​​stock bubble may be losing steam as competition from China intensifies. His focus is on Kimi K3, a new AI model that is expected to challenge American companies' products with a more competitive price and approach.

These statements should be treated as market opinion, not evidence that a bubble has burst. Schiff is known for his critical views on risky asset valuations, monetary policy, technology, and the crypto market.

However, his argument touches on an important issue. AI stock valuations depend not only on the growth in technology adoption, but also on the company's ability to maintain:

• Model advantages.
• Service price.
• Computational margin.
• Ecosystem dominance.
• Customer loyalty.
• Access to the chip.
• The rate of return on capital expenditure.

If a competitor's model offers similar capabilities at a lower cost, investors may lower their margin and growth estimates for the American AI company. Small changes in these projections can have a significant impact on stocks trading at high valuations.

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What is K3 AI Chemistry?

Kimi K3 is a flagship model developed by a Chinese AI company. It was introduced in July 2026, boasting a scale of 2.8 trillion parameters, multimodal capabilities, and a context capacity of up to one million tokens. Kimi K3 is designed for long-term coding, analysis, knowledge-based tasks, and complex reasoning.

Its presence is attracting attention because it shows that the frontier model competition no longer only involves American companies such as OpenAI, Google, Anthropic, Meta, and Microsoft.

Sumber AI Generated Image

Demand for Kimi K3 grew so rapidly that service providers temporarily limited new subscriptions because computing capacity couldn't keep up with the number of users. This situation highlights two things: the model is gaining traction, but running advanced AI services still requires extensive computing infrastructure.

The Kimi K3 isn't proof that GPU demand is going away. Rather, its popularity suggests that new models may face capacity constraints as users increase.

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Why Could Kimi K3 Disrupt American AI Stocks?

The impact of Kimi K3 extends beyond its technical capabilities. This model could change market expectations regarding costs, competition, and the economic power of AI companies.

1. Reducing the Perception of AI Model Scarcity

High valuations often arise when investors perceive only a few companies capable of building frontier models. If Chinese companies can offer competitive technology, this scarcity will be reduced.

Increasingly accessible modeling capabilities could shift economic value away from modelers and towards companies that have:

• User distribution.
• Exclusive data.
• Cloud infrastructure.
• Software integration.
• Corporate relations.
• Products with real benefits.

This shift may benefit AI users, but reduce the pricing power of model developers.

2. Triggering Price Competition

A cheaper model could fuel API and subscription price wars. Companies may have to lower their rates to retain customers.

Price cuts aren't always bad. Lower costs can expand AI adoption and increase demand. However, increased volume doesn't necessarily offset declining margins.

Investors need to see whether AI companies are able to lower inference costs faster than service prices are falling.

3. Questioning Large Capital Expenditures

American technology companies are investing heavily in data centers, chips, electricity, networking, and model development. The five major hyperscalers are expected to spend about half a trillion dollars by 2026 on technology and AI projects.

Such expenditures may be justified if they generate commensurate revenue growth and cash flow. However, if lower-cost models are able to deliver similar results, investors will question the payback period of expensive infrastructure.

4. Strengthening China's AI Competition

Kimi K3 demonstrated that chip access restrictions haven't halted Chinese AI innovation. Developers can find efficiencies through model architecture, software optimization, alternative chip use, and compute management.

This competition may influence the assumption that American companies will maintain technological dominance without significant pressure.

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Is K3 Chemistry Really a Trigger for Correction?

Kimi K3 may be a catalyst for sentiment, but it would be incorrect to call him the sole cause of AI's stock correction.

The technology market is also facing pressure from:

• Valuation is already high.
• Concerns over capital expenditure.
• The uncertainty of AI monetization.
• Interest rate level.
• Rising bond yields.
• Geopolitical risks.
• The index concentrates on a few large stocks.
• Profit taking action after a long rise.

The global AI stock index rose by around 45% between April and May 2026 before declining in June. This movement suggests that sector sentiment was already fragile before Kimi K3 became a market concern.

In other words, Kimi K3 is more appropriately viewed as new triggers that test old narratives, is not the sole cause of the AI ​​stock bubble.

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The Impact of K3 Chemistry on Nvidia Stock

Nvidia is at the center of AI infrastructure growth because the company's GPUs are used for model training and inference. Therefore, news of more efficient AI models is often perceived as a threat to chip demand.

However, the impact is not as simple as “cheaper models mean lower GPU demand”.

A more efficient model could yield two possibilities:

Negative Scenario for Nvidia

Chip demand can slow down if:

• The model requires less GPU.
• Companies are reducing the size of data centers.
• Customers use alternative chips.
• Computing providers' margins are declining.
• AI shopping is not generating enough profits.
• Chinese companies are reducing reliance on American technology.

Positive Scenario for Nvidia

Computational demand may actually increase if:

• Lower AI costs attract more users.
• The number of AI applications and agents is increasing.
• The volume of inference is growing faster.
• More companies are building their own models.
• Competition drives global data center investment.

Kimi K3's experience facing capacity constraints after demand spiked supports the argument that model efficiency does not automatically eliminate the need for computing.

Therefore, Nvidia investors need to monitor inference volume growth, data center orders, margins, chip competition, and customers' ability to finance capital expenditures.

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Impact on Microsoft and OpenAI

Microsoft has significant exposure to AI through its cloud services, Copilot, data centers, and its relationship with OpenAI. New model competition could create both pressure and opportunity.

Risks for Microsoft

Microsoft could face pressure when:

• Customers choose cheaper models.
• Data center costs are rising faster than revenues.
• Using Copilot did not result in the expected monetization.
• Companies must support more models with lower margins.
• Reliance on a single model developer loses strategic value.

Opportunities for Microsoft

As a cloud and platform provider, Microsoft can benefit by offering a variety of models. If customers use Kimi K3 or an open model through its infrastructure, Microsoft can still generate computing revenue.

OpenAI faces different challenges. As a model development company, its position is more sensitive to price competition and technical capabilities. Expenses for training and running models must be offset by revenue from subscriptions, APIs, enterprise, and new products.

Market reports indicate a significant gap between spending and monetization at a number of private AI companies. This is concerning because high valuations require a reliable path to profitability.

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Has the AI ​​Stock Bubble Burst?

There is not yet sufficient basis to declare that the entire AI stock bubble has burst.

The decline in technology stocks could be:

• Normal correction.
• Sector rotation.
• Valuation adjustment.
• Response to competition news.
• The beginning of a longer bearish trend.
• The bursting of a bubble in a particular stock group.

Bubbles don't necessarily burst simultaneously. Some companies may experience significant declines, while others continue to grow due to improved revenue, cash flow, and market position.

A recent study on AI valuations concluded that the sector exhibits a combination of truly transformative technology and bubble-like fragility. These risks are more concentrated in specific segments or companies, rather than necessarily across the entire industry.

This approach is more realistic than choosing one of the extreme conclusions: all AI stocks must be a bubble or there is no bubble at all.

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Arguments in Support of the AI ​​Bubble

Several indicators reinforce concerns about an AI stock bubble.

Valuation Is Above Historical Average

Technology stocks are trading at valuations higher than historical averages. When valuations are high, even slightly below-expected financial results can trigger a major decline.

Very Aggressive Infrastructure Spending

Companies spend heavily on chips, data centers, energy, and model development. Not all of these expenditures yield measurable profits.

Concentrated Market

Several large companies have significant weightings in the US index. A decline in Nvidia, Microsoft, Alphabet, Amazon, MetaTrader, or semiconductor companies could weigh on the broader index.

Monetization Hasn't Lived Up to Expectations

Many companies have adopted AI, but the benefits to productivity and profits are not always visible. Market expectations may be moving faster than economic realization.

Competition Increases

Kimi K3, open models, and Chinese developers can lower prices and shorten the technological lead period of incumbents.

The Argument That AI Has Not Become a Systemic Bubble Yet

On the other hand, the current conditions have important differences from the dot-com bubble.

Largest technology companies:

• Already generating huge revenue.
• Have positive cash flow.
• Have global customers.
• Finance most investments from profits, not debt.
• Have other businesses outside of AI.
• Mastering cloud, software, advertising, and infrastructure.

By the end of 2025, technology stock valuations will be above historical averages, but still below the extreme levels of the dot-com era. Large companies' capital expenditures will also still be largely funded by their own revenues and cash flow.

This doesn't make stocks risk-free. However, a sharp correction doesn't necessarily mean the AI ​​industry will collapse like many internet companies did in the early 2000s.

AI Bubble Indicators to Monitor

Investors shouldn't judge a bubble based solely on a single news story or market leader's statement. The following five indicators are more useful:

1. Income Growth

Check whether AI revenue is growing in line with the stock price. Customer growth without adequate monetization isn't enough.

2. Profit Quality

Compare net income with cash flow. Profit based on accounting adjustments has a different quality than cash actually received.

3. Valuation

Compare price-to-earnings, price-to-sales, and free cash flow yield with company growth and historical averages.

4. Sustainability of Capex

Assess whether data centers and chips are generating sufficient revenue. Companies that must continue to borrow to maintain spending face higher risks.

5. Interest Rate

Growth stock valuations are sensitive to interest rates. Rising bond yields can reduce the present value of future profits.

These five indicators are also used to differentiate between fundamental growth and speculative euphoria.

Strategies for Facing the Risk of an AI Market Crash

Investors shouldn't exit all AI stocks just because a bubble warning appears. A more measured approach includes:

• Avoid over-concentration on one stock.
• Differentiate between chip manufacturers, cloud, application, and model developers.
• Check revenue growth and cash flow.
• Evaluate the valuation before buying.
• Avoid excessive use of debt or leverage.
• Set an investment horizon.
• Prepare for a price drop scenario.
• Monitor capital expenditures and margins.
• Don't buy just because of the AI ​​label.
• Perform rebalancing when the stock weight is too large.

A company with good technology isn't necessarily a good investment if its stock price is already overpriced. Conversely, a price drop doesn't automatically make a stock cheap if earnings expectations also fall.

To keep up with developments in the technology market, digital assets, and global sentiment that can influence investments, you can register at Bittime and check the latest news regularly. Use market information as research material, not as a guarantee of price direction.

AI Stock Prospects after Kimi K3's Arrival

Kimi K3 could accelerate the structural change of the AI ​​industry. Economic value may shift from the basic model to distribution, data, business integration, chips, energy, and applications that truly solve user problems.

Companies that rely solely on exclusive access to a single model may lose their advantage. Conversely, companies with customer networks, unique data, integrated products, and the ability to manage multiple models have the potential to be more resilient.

Competition can also expand the market. As AI costs fall, more companies can afford to use the technology. Growing adoption can increase demand for cloud computing, chips, networking, security, and software.

Thus, the presence of K3 isn't necessarily bad news for all sectors. Its impact will vary across industries.

Conclusion

Peter Schiff's warning about an AI stock bubble highlights the real risks of high valuations, aggressive capital spending, and Chinese AI competition. Kimi K3's presence reinforces concerns that frontier modeling capabilities could become cheaper and no longer the domain of a handful of American companies.

However, Kimi K3 isn't enough to prove the entire AI bubble has burst. Many market leaders still have strong revenue, profits, cash flow, and core businesses. The high demand for Kimi K3 also demonstrates that efficient models still require significant computing capacity when widely deployed.

Investors should evaluate each company based on its valuation, revenue growth, earnings quality, cash flow, margins, and the ability of its capital expenditures to generate profits. Competition from Kimi K3 could trigger a correction, but the company's fundamentals will determine whether the decline is temporary or develops into a deeper AI market crash.

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FAQ

What is an AI stock bubble?

An AI stock bubble occurs when the valuation of AI stocks increases faster than their underlying revenue, earnings, and cash flow. Bubbles typically stem from overly optimistic future expectations.

What is the relationship between Kimi K3 and AI stock?

Kimi K3 is intensifying global AI model competition and could drive down service prices. This has investors reassessing margins and capital expenditures at American AI companies.

Can Kimi K3 bring down Nvidia stock?

Not automatically. Efficient models can reduce the compute requirements per task, but broader AI deployments can also increase the overall demand for GPUs and data centers.

Will AI stocks crash in 2026?

There's no certainty that all AI stocks will crash. The risk of a correction remains high for companies with expensive valuations, weak monetization, and heavy reliance on growth expectations.

How to deal with the risk of an AI stock bubble?

Diversify your portfolio, evaluate valuations, check cash flow, and avoid excessive leverage. Don't buy a stock just because the company uses AI.