Cerebras becomes the world’s fastest host for DeepSeek R1, outpacing Nvidia GPUs by 57x


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Cerebras Systems announced today it will host DeepSeek’s breakthrough R1 artificial intelligence model on U.S. servers, promising speeds up to 57 times faster than GPU-based solutions while keeping sensitive data within American borders. The move comes amid growing concerns about China’s rapid AI advancement and data privacy.

The AI chip startup will deploy a 70-billion-parameter version of DeepSeek-R1 running on its proprietary wafer-scale hardware, delivering 1,600 tokens per second — a dramatic improvement over traditional GPU implementations that have struggled with newer “reasoning” AI models.

Response times of leading AI platforms, measured in seconds. Cerebras achieves the fastest response at just over one second, while Novita’s system takes nearly 38 seconds to generate its first output — a critical metric for real-world applications. (Source: Artificial Analysis)

Why DeepSeek’s reasoning models are reshaping enterprise AI

“These reasoning models affect the economy,” said James Wang, a senior executive at Cerebras, in an exclusive interview with VentureBeat. “Any knowledge worker basically has to do some kind of multi-step cognitive tasks. And these reasoning models will be the tools that enter their workflow.”

The announcement follows a tumultuous week in which DeepSeek’s emergence triggered Nvidia’s largest-ever market value loss, nearly $600 billion, raising questions about the chip giant’s AI supremacy. Cerebras’ solution directly addresses two key concerns that have emerged: the computational demands of advanced AI models, and data sovereignty.

“If you use DeepSeek’s API, which is very popular right now, that data gets sent straight to China,” Wang explained. “That is one severe caveat that [makes] many U.S. companies and enterprises…not willing to consider [it].”

Cerebras demonstrates dramatic performance advantages in output speed, processing 1,508 tokens per second — nearly six times faster than its closest competitor, Groq, and roughly 100 times faster than traditional GPU-based solutions like Novita. (Source: Artificial Analysis)

How Cerebras’ wafer-scale technology beats traditional GPUs at AI speed

Cerebras achieves its speed advantage through a novel chip architecture that keeps entire AI models on a single wafer-sized processor, eliminating the memory bottlenecks that plague GPU-based systems. The company claims its implementation of DeepSeek-R1 matches or exceeds the performance of OpenAI’s proprietary models, while running entirely on U.S. soil.

The development represents a significant shift in the AI landscape. DeepSeek, founded by former hedge fund executive Liang Wenfeng, shocked the industry by achieving sophisticated AI reasoning capabilities reportedly at just 1% of the cost of U.S. competitors. Cerebras’ hosting solution now offers American companies a way to leverage these advances while maintaining data control.

“It’s actually a nice story that the U.S. research labs gave this gift to the world. The Chinese took it and improved it, but it has limitations because it runs in China, has some censorship problems, and now we’re taking it back and running it on U.S. data centers, without censorship, without data retention,” Wang said.

Performance benchmarks showing DeepSeek-R1 running on Cerebras outperforming both GPT-4o and OpenAI’s o1-mini across question answering, mathematical reasoning, and coding tasks. The results suggest Chinese AI development may be approaching or surpassing U.S. capabilities in some areas. (Credit: Cerebras)

U.S. tech leadership faces new questions as AI innovation goes global

The service will be available through a developer preview starting today. While it will be initially free, Cerebras plans to implement API access controls due to strong early demand.

The move comes as U.S. lawmakers grapple with the implications of DeepSeek’s rise, which has exposed potential limitations in American trade restrictions designed to maintain technological advantages over China. The ability of Chinese companies to achieve breakthrough AI capabilities despite chip export controls has prompted calls for new regulatory approaches.

Industry analysts suggest this development could accelerate the shift away from GPU-dependent AI infrastructure. “Nvidia is no longer the leader in inference performance,” Wang noted, pointing to benchmarks showing superior performance from various specialized AI chips. “These other AI chip companies are really faster than GPUs for running these latest models.”

The impact extends beyond technical metrics. As AI models increasingly incorporate sophisticated reasoning capabilities, their computational demands have skyrocketed. Cerebras argues its architecture is better suited for these emerging workloads, potentially reshaping the competitive landscape in enterprise AI deployment.



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