The Hangzhou startup released preview versions of both models on Hugging Face on Friday. V4-Pro claims top performance on coding and maths among open models, trails only Gemini 3.1-Pro for world knowledge, and falls “marginally short” of GPT-5.4 and Gemini 3.1-Pro, a gap DeepSeek says is “approximately 3 to 6 months.” Both models are open-source.

DeepSeek, the Hangzhou-based AI startup that upended Silicon Valley with its R1 model in January 2025, released preview versions of its latest flagship models on Friday, approximately one year after that original shock.

The company posted DeepSeek-V4-Pro and DeepSeek-V4-Flash on Hugging Face, describing the release as the most powerful open-source AI platform available and a direct challenge to rivals from OpenAI to Anthropic.

Both models follow the open-source model used by their predecessors, meaning developers are free to use and modify the source code.

The headline technical advance in V4 is the Hybrid Attention Architecture, a technique DeepSeek says improves the model's ability to retain context across long conversations.

Combined with a 1-million-token context window, sufficient to process an entire codebase or a book-length document in a single prompt, the architecture is designed for agentic and long-horizon reasoning tasks, where previous models degraded in quality as context length increased. The Flash variant is optimised for speed and cost efficiency; the Pro variant for peak capability.

DeepSeek's own benchmark positions V4-Pro as the strongest open-source model in coding and mathematics, with performance that trails only Google's closed-source Gemini 3.1-Pro in world knowledge.

Against the current closed-source frontier, OpenAI's GPT-5.4 and Gemini 3.1-Pro — the company says V4-Pro falls only “marginally short,” and offers a candid self-assessment: its “developmental trajectory” trails state-of-the-art frontier models by approximately 3 to 6 months.” 

That framing is unusual in AI model releases, which typically emphasise comparisons where the new model leads. That DeepSeek is publishing a gap estimate rather than claiming parity reflects either unusual intellectual honesty or a strategic move to set conservative expectations ahead of independent evaluation.

The chip story is the geopolitically charged element. DeepSeek worked with Chinese AI chipmakers Huawei and Cambricon to optimise V4 for their latest hardware, according to Reuters, citing The Information.

The company did not give Nvidia or AMD early access for optimisation, a reversal of standard industry practice in which Western chipmakers are typically the first to receive new model weights for performance tuning.

Running a frontier-class model at this scale on Huawei's Ascend chips, rather than on Nvidia H100s or H200s,  would be a significant proof of concept for China's domestic AI hardware supply chain, which has been under US export restrictions since October 2022. The V4 release does not end that geopolitical constraint, but it tests its limits in a commercially visible way.

The timing of the release, Friday, 24 April 2026, approximately one year after DeepSeek-R1, is deliberate. DeepSeek-R1's January 2025 launch erased roughly $600 billion from Nvidia's market capitalisation in a single day, as investors recalibrated their assumptions about the compute required to build frontier AI.

Marc Andreessen called it “AI's Sputnik moment.” The practical claim was that a Chinese lab had matched OpenAI's best reasoning model while spending less than $6 million on compute, a figure some analysts disputed but which nonetheless reset global assumptions about the economics of frontier AI development.

V4 arrives into a different market: one where OpenAI has released GPT-5.5 on the same day, where Anthropic is valued at $1 trillion on secondary markets, and where the US-

China AI competition has become an explicit dimension of trade and technology policy. DeepSeek's second act is landing in a much more contested arena than its first.

Both models are preview releases, not final production versions. Independent benchmarking has not yet been completed as of the time of writing, and DeepSeek's own benchmarks should be treated as preliminary until third-party evaluation confirms them.

The same caveat applied to R1, whose claims were broadly validated by external testing within days of release. Whether V4 holds up to the same scrutiny will be clear within the week.