Nvidia's new AI model triggers a surge in quantum computing stocks, with quantum concept stocks in China, South Korea, and Japan rising 8%-30%.

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Nvidia has launched the world’s first open-source AI quantum computing model family, Ising, igniting the concept stocks of quantum computing in Asian markets. Related stocks in China, South Korea, and Japan soared up to the 30% daily limit.

This Tuesday, Nvidia officially released the Ising model, designed to address two key bottlenecks restricting the practical use of quantum computing—quantum processor calibration and quantum error correction decoding. After the announcement, Asia-Pacific tech stocks reacted immediately, with quantum computing-related concept stocks leading the gains.

Boosted by the news, Korea's Axgate and ICTK shares once hit the 30% daily upper limit; China’s USTC Guochuang and Guodun Quantum, and Japan’s Fixstars saw gains over 8%. Asia-Pacific tech stocks rebounded overall that day, with a calmer Middle East situation providing additional market support. Notably, this round of gains focused mainly on quantum concept stocks in software, IT, and cybersecurity—not on quantum hardware companies themselves.

Nvidia Bets on AI-Quantum Fusion

Nvidia’s newly released Ising is the first open-source AI model family built atop its CUDA-Q quantum development platform, including two customizable models specifically designed for quantum processor calibration and quantum error correction decoding.

Jensen Huang positions Ising as the quantum machine’s "control plane" and "operating system," believing AI is the critical path to scaling quantum computing for broader applications.

Ising is released as open source, allowing researchers and enterprises to develop and customize on its foundation without relying on closed platforms. The name is derived from the Ising model in physics—a classic mathematical framework that greatly simplifies the understanding of complex physical systems. Nvidia uses this name to emphasize its core value proposition in simplifying the quantum system’s control layer.

Double Improvement in Decoding Speed and Accuracy

Qubits are highly susceptible to external interference; currently, quantum processors experience one error per thousand computations.

Nvidia states that for quantum computing to become truly practical, this error rate must be reduced to just one per trillion computations—a key engineering challenge on the road to commercializing quantum computing.

According to Nvidia’s disclosed data, the Ising model achieves up to a 2.5-fold improvement in speed and a 3-fold improvement in precision during error correction decoding. The Ising Calibration model is 15 times smaller than comparable solutions, and Ising Decoding requires 10 times less training data. This combination of parameters means lower deployment thresholds and faster progress towards practical application.

Currently, institutions such as Fermilab, Harvard University, Lawrence Berkeley National Laboratory, and quantum tech companies Infleqtion and IQM Quantum Computers have announced adoption of the model.

Commercialization Still a Long Road Ahead

Despite feverish market sentiment, institutions remain cautious. Robert Lea, an analyst with Bloomberg Industry Research, said, "While these tools may accelerate relevant advances, practical large-scale quantum computing is still a long way from implementation."

This assessment matches the current industry status: the stability of qubits at the hardware level, the overhead of error correction, and the difficulty of system integration determine that this sector will focus on technological accumulation in the short term, with a long cycle for commercialization returns. For the concept stocks hyped by this, the gap between fundamental support and sentiment-driven gains is a risk that investors need to carefully consider.

Market Size: Breaking $10 Billion in 2030

According to Stratistics Market Research Consulting, the global quantum computing market will surge from about $1.7 billion in 2024 to over $11 billion in 2030. This growth heavily depends on continuous breakthroughs in core engineering challenges such as quantum error correction and scalability—precisely the direction Nvidia is targeting in its deployment.

For investors, the release of Ising further enriches Nvidia’s long-term growth narrative beyond its AI infrastructure, clarifying its strategic position in the emerging quantum computing arena. However, there remain plenty of engineering challenges between model release and industry implementation, and whether the short-term breakout of quantum computing concept stocks can secure sustained fundamental support remains to be seen.

Risk Warning and DisclaimerThe market is risky, and investment requires caution. This article does not constitute personal investment advice, nor does it take into account individual users’ specific investment goals, financial condition, or needs. Users should consider whether any opinions, viewpoints, or conclusions in this article are suitable for their particular situation. Investing accordingly is at your own risk. ```