SpikingBrain 1.0: China’s New Leap Toward Human-Like Artificial Intelligence

The SpikingBrain 1.0 model marks a new milestone in the evolution of artificial intelligence (AI) in China. It reflects a strategic shift toward developing AI systems that emulate the way the human brain thinks and processes information. Based on neural processing inspired by electrical impulses in brain cells, this model achieves exceptional speed—over 100 times faster than traditional models—while consuming significantly less energy. Its importance extends beyond technical capabilities; it also relies entirely on domestically produced chips, aligning with Beijing’s broader goal of reducing dependence on Western technologies amid growing export restrictions on advanced semiconductors.

China’s Objectives

Unveiled in September 2025, the SpikingBrain 1.0 model aims to fulfill several key objectives:

1. Strengthening China’s Technological Independence

The model was developed by a team led by Li Guoqi and Xu Bo at the Institute of Automation, Chinese Academy of Sciences. It was trained using hundreds of GPUs provided by Shanghai-based MetaX, demonstrating China’s ability to build advanced models without relying on U.S. companies like Nvidia, whose chip exports were previously restricted by Washington. Although the Trump administration later eased these restrictions, Beijing continues to replace foreign components as part of a long-term strategy to safeguard its technological sovereignty.

2. Reducing Operational Costs and Improving Efficiency

Unlike massive Transformer-based language models such as ChatGPT, SpikingBrain 1.0 operates using Spiking Neural Networks (SNNs) — a technology that mimics the human brain’s activity. Instead of activating the entire network simultaneously, it only triggers the necessary neurons (computational units) when needed, just like biological brain cells. Different neural clusters are responsible for specific tasks such as coding or mathematical reasoning, enabling the model to function more efficiently and intelligently.

3. Achieving Qualitative Superiority Over Western Models

According to CGTN, China’s English-language state media, SpikingBrain 1.0 represents a major technological leap. It requires only about 2% of the pre-training data used by traditional large language models, thanks to its sparse computational design. Reports from Yicai Global indicate that for inputs containing one million tokens, SpikingBrain produced the first output token 27 times faster than a conventional model. CGTN further noted that it can process long tasks up to 100 times faster than traditional architectures.

4. Cementing China’s Leadership in Neuromorphic AI

Neuromorphic AI, a field that replicates the brain’s structure and information-processing methods, first emerged in the United States during the 1980s. However, China has rapidly risen as a key player. A 2025 report by Research and Markets titled “Advanced AI Electronics Technologies 2026–2036” identifies China as one of the leading forces in neuromorphic AI, highlighting the Institute of Automation’s creation of the world’s first brain-like model as a strategic milestone toward technological self-reliance and more human-like AI.

5. Building Sustainable and Eco-Friendly AI

Energy consumption is one of the greatest challenges in AI development—training large models can require hundreds of megawatts of electricity. SpikingBrain 1.0 addresses this by activating only the required portions of the network, drastically reducing power use, cooling needs, and carbon footprint. This innovation makes it a promising step toward environmentally sustainable AI aligned with global climate goals.

6. Leading the Next Technological Transformation

The Research and Markets report anticipates a global turning point in AI between 2026 and 2036, as conventional processors become inadequate for the massive computational demands of large language models and real-time autonomous systems. The world is shifting toward specialized technologies, including neuromorphic and quantum computing. While Western powers—especially the United States—still lead, China’s rapid academic progress and strategic investments demonstrate its ambition to move from follower to leader in this new era.

Broader Implications

Although SpikingBrain 1.0 remains in its experimental phase, researchers have created two versions: a 7-billion-parameter model and a 76-billion-parameter version for professional and public testing. Its introduction could have far-reaching technological, political, and economic consequences:

1. Accelerating the U.S.–China Technological Race

Since 2019, the U.S. has maintained clear dominance in AI, producing over half of the world’s leading models. American giants have invested over $212 billion in R&D, while AI startups raised $90 billion in 2024 alone. The U.S. also leads in AI talent, with 500,000 experts and 45 GW of data center capacity.
However, China is narrowing this gap through centralized planning rather than private-sector leadership. Since 2019, Beijing has invested roughly $132 billion in AI and allocates $60 billion annually to institutional R&D. As a result, China now hosts 15 of the world’s top 40 models, employs 18% of global AI researchers, and possesses the second-largest data center capacity (≈20 GW). Models like DeepSeek and SpikingBrain 1.0 showcase China’s progress toward a new generation of AI that transcends traditional approaches.

2. Encouraging Global AI Investment

The AI race now extends beyond the U.S., China, and Europe to include the Global South, where nations are developing sovereign, locally adapted AI systems. The Middle East stands out—countries like the UAE, Saudi Arabia, and Qatar have launched major initiatives to build world-class data centers and develop indigenous AI models.

3. Redefining AI Performance Standards

SpikingBrain 1.0 combines hybrid-linear attention mechanisms, conversion-based training, and spiking neurons, enabling performance comparable to massive Transformer models but with unprecedented efficiency. Western models may continue to innovate, but their reliance on extreme computational power makes them unsustainable long-term. This gives China’s model a strategic edge for the future.

4. Reducing Dependence on Western Supply Chains

China’s approach to the ongoing tech war with the U.S. emphasizes self-sufficiency—advancing domestic AI chips, electric vehicle technologies (e.g., BYD), and rare-earth export controls under the “Made in China 2025” strategy. The SpikingBrain 1.0 model’s independence from Nvidia chips represents a tangible success in decoupling from Western supply chains, strengthening China’s resilience against potential trade restrictions.

5. Advanced Applications Across Multiple Fields

Thanks to its ability to process ultra-long sequences, SpikingBrain 1.0 can be applied to fields such as legal and medical document analysis, high-energy particle physics, and DNA sequence modeling, according to leading Chinese researchers involved in its development.

Conclusion

While SpikingBrain 1.0 marks a groundbreaking scientific milestone and demonstrates China’s accelerating march toward technological self-reliance, challenges remain. Experimental success doesn’t guarantee smooth commercial deployment, especially amid intense U.S. competition and continued export restrictions.
However, by combining domestic innovation with advanced AI architectures, Beijing now holds a genuine opportunity to reshape the global AI race—provided it continues investing in research, development, and large-scale practical applications.