Tag: DeepSeek

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Technology

DeepSeek launches V4 AI model, challenges US giants

Chinese AI startup DeepSeek has launched its latest large language model, DeepSeek V4, in a fresh challenge to major US players such as OpenAI, Google and Anthropic. The release strengthens China’s growing push to compete in the fast-moving artificial intelligence race.

The company introduced two versions of the model, V4 Pro and V4 Flash. While the Pro version is aimed at advanced reasoning, coding and research tasks, the Flash version is designed to be faster and cheaper for lighter everyday use. Both versions are currently available in preview mode.

DeepSeek said the new model can process very large amounts of text at once, allowing users to analyse long reports, documents and code files more efficiently. This could make the model attractive to businesses, researchers and developers handling large workloads.

The company also claimed improved performance in coding, logic and knowledge-based tasks compared with earlier versions. Independent testing of these claims is still awaited, but the launch has already drawn attention across the tech industry.

Another key feature is compatibility with Huawei’s Ascend chips, showing China’s efforts to reduce dependence on US chipmaker Nvidia amid export restrictions.

DeepSeek gained global visibility last year by offering lower-cost AI models that surprised the market with strong performance. Its latest launch is expected to increase pricing pressure on bigger rivals and expand AI choices for users worldwide.

The V4 release highlights how competition in artificial intelligence is no longer limited to Silicon Valley, with Chinese firms now emerging as serious challengers.

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1 Minute-Read

DeepSeek withholds AI model from US firms

Chinese AI startup DeepSeek has reportedly decided not to share its latest AI model with major US chipmakers, including Nvidia and Advanced Micro Devices.

Sources said the company instead gave early access to selected Chinese hardware partners, such as Huawei Technologies, ahead of the model’s expected launch.

Typically, AI developers provide early versions of new models to global chip firms to improve compatibility and performance. The move is seen as part of China’s push to strengthen domestic technology capabilities amid ongoing US-China trade and technology tensions.

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Beyond

China’s DeepSeek reveals efficient AI training

Chinese AI startup DeepSeek has introduced a new way to train large AI models more efficiently. The approach, called Manifold‑Constrained Hyper‑Connections (mHC), helps models learn faster while using less computing power and energy. This is especially important as China faces limits on buying the latest AI chips from abroad due to US export restrictions.

The research paper, co‑authored by founder Liang Wenfeng and 18 other researchers, tested mHC on AI systems ranging from 3 to 27 billion parameters. The method stabilises training and avoids excessive computing costs, making it easier to build very large AI models without huge energy bills.

DeepSeek has a history of surprising the AI industry. Its 2025 R1 reasoning model was developed at a much lower cost than similar models from US companies. Experts now expect the next model, R2, to launch around China’s Spring Festival in February. The new mHC training method is expected to power this model, making it faster and more efficient.

China’s AI firms continue to face challenges due to limited access to advanced semiconductors. This has pushed companies like DeepSeek to create innovative, resource‑saving techniques to stay competitive globally.

Analysts suggest that R2 could make a significant impact internationally, even as companies like Google and OpenAI release high‑performance models. China’s lower-cost, efficient AI models are already gaining recognition in global rankings, showing the country’s growing technical capabilities.

DeepSeek has shared its research on open platforms like arXiv and Hugging Face, reflecting a trend of more openness and collaboration among Chinese AI developers.

The new method could set a benchmark for energy-efficient, large-scale AI training, helping China expand its AI capabilities despite hardware limitations.

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