Kimi K3 is Here. Could This Be the "DeepSeek 2.0" Moment for US Stocks?

Last Friday, the US-listed memory chip sector collectively declined again.

On the surface, this appears to be merely a continuation of the chip stock correction over the past two weeks. However, beneath the surface, a new variable from China is roiling the entire market: Kimi K3, released by Moonshot AI on July 17th.

This open-source large language model, boasting 2.8 trillion parameters, topped the global code evaluation leaderboard CodeArena, directly surpassing Anthropic's Claude Fable 5. What made the market even more unsettled was its cost: a single task inference cost is only $0.94, less than half of Claude Opus 4.8, and roughly on par with OpenAI's GPT-5.6 Sol.

Larger scale, stronger coding capabilities, and cheaper inference costs – does this combination sound familiar?

In response, JPMorgan directly labeled it a "DeepSeek 2.0 moment."

1. The Traumatic Memory of DeepSeek 1.0: Bloodbath in Chip Stocks and Bitcoin

To understand why the term "DeepSeek 2.0" can keep Wall Street up at night, we must first revisit what happened in March and April 2025.

Last year, DeepSeek achieved performance levels close to GPT-4 with extremely low training costs. When the news broke, the market was instantly plunged into collective panic over the overvaluation of AI chips:

• Nvidia's stock price plummeted from a high of around $135 to near $85, a decline of nearly 40%.
• Bitcoin fell from its all-time high of nearly $110,000 to around $75,000.

The logical chain was simple: If Chinese companies can train top-tier models with fewer chips and lower costs, will US cloud vendors and tech giants still need to continue their frenzied purchasing of GPUs and HBM? Was the AI infrastructure arms race an overpriced bubble from the start?

The market gave a clear answer at that time – a crash.

Now, Kimi K3 has emerged with the labels of "world's largest open-source model + lower inference cost," with its parameter scale even more staggering than DeepSeek's. Once fear psychology is triggered, selling pressure in the chip sector spreads rapidly.

2. SemiAnalysis's Contrarian Interpretation: K3 Is Not Destroying GPU Demand, It's Amplifying It

But there is another side to the story.

Semiconductor research firm SemiAnalysis recently provided a completely opposite analytical framework. Their core argument is that K3's massive parameter scale and inference architecture, rather than weakening demand for high-end AI hardware, could become another long-term demand engine for Nvidia and its supply chain.

Breaking it down, SemiAnalysis's judgment is based on the following key facts:

First, a model that is "too large" actually requires more hardware.

K3's parameter count exceeds 2.8 trillion, with just the model weights requiring over 1.5TB of HBM (High Bandwidth Memory) space. Currently, the HBM capacity of a single top-tier Nvidia GPU is far from sufficient to load the entire model. Even in scenarios with relatively limited user concurrency, KV caches still need significant offloading to CPU DDR5 memory and NVMe storage devices – HBM space is not surplus but is actually stretched thin.

Second, inference deployment places extremely high demands on hardware scale.

Moonshot AI previously revealed that for K3 to achieve efficient inference deployment, it requires a large-scale extended domain architecture consisting of at least 64 high-end chips. This level of cluster scale aligns highly with the design philosophy of rack-level AI systems like Nvidia's GB200/GB300 NVL72. In other words, K3 is not "replacing" high-end hardware, but rather "defining" the use case for the next generation of high-end hardware.

Third, there is a misinterpretation of "linear attention weakening GPU demand."

The market previously held a popular view: more efficient attention mechanisms (like linear attention) mean less computation, hence declining demand for GPUs. SemiAnalysis believes this logic has a fundamental flaw. The real impact could be quite the opposite – more efficient model architectures lower the cost of a single inference, significantly lowering the barrier for AI application implementation, thereby driving demand for broader, larger-scale AI deployments across more enterprises and scenarios.

From a macro perspective: Model efficiency improvement → Unit cost reduction → AI application explosion → Total computing power demand rises, not falls. This is a recurring script in the history of the semiconductor industry – every "efficiency revolution" has ultimately led to a larger wave of hardware investment.

3. What is the Market Trading On? The Tug-of-War Between Fear and Rationality

The current market is in a state of extreme fragmentation.

The bears' logic is intuitive: Kimi K3 once again proves the breakthrough capability of Chinese AI companies on the path of low cost and high efficiency. If this trend continues, AI companies will eventually reassess their capital expenditure (capex) plans. The "supply shortage" narrative for AI chips might be replaced by a "good enough" narrative.

The bulls' rebuttal is equally compelling: K3 is not a scaled-down version of DeepSeek, but a scaled-up one – it is so vast that high-end hardware clusters are absolutely essential for its operation. SemiAnalysis's research indicates that HBM is not in surplus but might be in even scarcer supply. Furthermore, if AI applications become widely adopted due to lower costs, total computing power demand will grow exponentially.

Both sides have valid points. And this is precisely the market's most painful moment – when two completely opposite logics both find solid data support, prices are not pricing fundamentals but rather emotions.

4. Facing a Fragmented Market, You Don't Have to Bet on One Direction

In such a highly uncertain environment, the hardest part is not judging the direction, but controlling the cost of being wrong.

Bulls say the correction in chip stocks is an "unjustified sell-off," while bears say the super cycle for AI chips has peaked. Both views have data and endorsements from well-known institutions. For the average investor, instead of gambling on one direction in this fog of information, a better approach is to ensure you aren't completely knocked out regardless of which direction the market moves.

The options functionality on the BIT platform precisely offers several core tools for this kind of "uncertainty trading":

① Holding Underlying Chip Stocks + Buying Put Options (Protective Put)

If you are heavily invested in Nvidia, Micron, or SK Hynix, but worry that the K3 event could trigger further decline, you can buy puts on the corresponding stocks. If the stock price continues to fall, the option profit can offset the loss on the shares; if it rebounds, you let the options expire, and your maximum loss is the premium paid.

② Buying Call Options in One Direction (Long Call)

If you agree with SemiAnalysis's "unjustified sell-off" logic and believe chip stocks will revert to fundamentals after emotional selling, you can directly buy call options. This uses much less capital than buying the underlying stock, betting on a rebound, with maximum loss capped at the premium.

③ Buying Put Options in One Direction (Long Put)

If you believe the "DeepSeek 2.0" narrative will fully replay and chip stocks have further room to fall, you can buy put options to short directly. No need for short-selling shares or margin calls; your maximum loss is the premium paid.

④ Buying Both Directions Simultaneously (Long Straddle)

If you are certain chip stocks will move significantly but are unsure whether up or down, you can buy both call and put options. As long as the price swing is large enough, profit from either direction could cover the cost of both options.

5. Closing Thoughts

The release of Kimi K3 has pushed AI chip investment to a critical crossroads. Is it the beginning of "DeepSeek 2.0" or the prelude to "demand being redefined"? The answer to this question may take time to fully emerge.

But until the answer is revealed, the most valuable thing investors can do is not to guess who will ultimately be right, but to prepare an exit strategy for their own potential misjudgment.

The BIT options feature is launching this week, covering core chip stocks such as Nvidia, Micron, and SK Hynix. Whether you are bullish or bearish, there are corresponding tools to express your view – while locking your worst-case loss within a range you can afford.

In an uncertain market, those with options hold the initiative.

Risk Disclaimer: The market conditions, valuation estimates, and product descriptions mentioned in this article are for reference only and do not constitute investment advice. Trading in US stocks and their derivatives involves market, leverage, and liquidity risks. Short selling stocks carries the risk of unlimited losses. Options trading carries the risk of total loss of premium. Past performance does not guarantee future results. Please make prudent decisions based on your own risk tolerance and consult a professional investment advisor when necessary.