DeepSeek has made its V4 Pro model publicly available, releasing it under the name DeepSeek-V4-Pro-0813 on its pricing page. The flagship model is equipped with a context window of 1 million tokens and a maximum output of 384 thousand tokens, defaulting to a thinking mode, but also providing an endpoint without thinking mode for latency-sensitive requests.
The combination of a 1 million token input and 384 thousand token output allows for processing and generating a significantly larger volume of material within a single request compared to the previous generation, which is particularly relevant for working with large codebases, extensive document corpora, and multi-stage agents.
DeepSeek has also integrated features that most agent developers expect: structured JSON output, tool calling support, Responses API, and compatibility with Anthropic-API. Furthermore, beta support for conversation prefix continuation and FIM completion has been implemented, with FIM limited to the non-thinking mode.
At the service level, endpoints compatible with both OpenAI and Anthropic are offered, allowing teams already using either standard to switch without needing to rebuild their infrastructure.
The pricing reflects a deliberate separation of tiers. The Pro model costs 0.025 yuan per million tokens when cached, 3 yuan for cache misses on input, and 6 yuan on output. In contrast, the Flash model is priced at 0.02, 1, and 2 yuan respectively, making Pro approximately three times more expensive than Flash for input and output cache misses.
Differences are also highlighted by parallelism limitations: Flash supports 2500 concurrent requests, whereas Pro is limited to 500. This ratio indicates a clearer product structure for the V4 family. Flash is geared towards high-frequency, high-throughput traffic where cost dominates, while Pro concentrates power on heavier reasoning tasks, long-context coding, and agent workflows, where the model has a greater performance reserve for use.
Nevertheless, the absolute price of Pro remains moderate by the standards of advanced models, allowing DeepSeek to offset costs after the recent price increase announcement while remaining cheaper than most foreign competitors. Thus, the V4 lineup presents a two-pronged offering: a low-cost, high-throughput Flash tier for scaling, and a more powerful Pro tier aimed at coding and agent tasks.
DeepSeek, a Chinese artificial intelligence company based in Hangzhou, has announced plans to construct a large data center in Inner Mongolia. This mega-center is estimated to have a computational capacity of one gigawatt and aims to increase the company's infrastructure to compete in the global AI market.
The undertaking will be established in Ulanqab, a city located approximately 350 kilometers northwest of Beijing. The plan includes both the creation of its own structure and the acquisition of additional capacity from other corporations. DeepSeek aims to begin some operations by the end of 2027 or early 2028.
This initiative is part of the global competition for computing power dedicated to artificial intelligence, where both American and Chinese companies are increasing their investments in large-scale data centers. DeepSeek seeks to consolidate its position after gaining recognition for developing AI models that require fewer computational resources.
The construction of this complex in Inner Mongolia ranks among the largest computing infrastructure projects linked to a Chinese AI company. An installation with a 1 GW capacity would surpass all operational AI data centers in the country, although it remains below American projects reaching capacities of 3 GW and 5 GW.
DeepSeek's scheme allows for the combination of proprietary facilities with leased space in third-party managed structures. Sources familiar with the matter indicate that more than ten companies already have planned projects in Ulanqab, as compiled by an independent source based on local government approvals.
Although the specific chip to be used has not been specified, Nvidia semiconductors are considered the dominant standard for data centers in the AI sector, while Huawei stands out as the main Chinese manufacturer in this area.
The choice of Ulanqab was motivated by the region's climatic conditions. With an average annual temperature close to 4 degrees Celsius, the location reduces the energy demand required to cool high-consumption servers, an attractive factor for companies wishing to operate large computing structures.
DeepSeek's expansion comes after the company gained international visibility by presenting AI models that, according to the company itself, demonstrated superior performance using fewer computational resources compared to its competitors. The strategy also included the development of open-source and low-cost services.
This advancement has placed the startup at the center of the technological dispute between China and the United States. Giants like OpenAI and Anthropic have invested billions of dollars in computing capacity, while Chinese groups such as Moonshot, Z.AI, Alibaba, and MiniMax are also seeking to expand their share in the sector.
DeepSeek's move occurs in an environment of growing geopolitical scrutiny. US authorities have raised suspicions that the company may have circumvented export restrictions by using Nvidia's Blackwell processors in a facility in Inner Mongolia, according to sources close to the matter.
Additionally, OpenAI and Anthropic have accused the Chinese startup of practicing a method called distillation, where results generated by existing AI models would be used to enhance new technologies.
The company has also begun preparations for a potential Initial Public Offering (IPO), potentially filing the application this year, as previously reported by Bloomberg News. Previously, the company had raised $7 billion, reaching an approximate valuation of $50 billion.
The construction of a data center of this magnitude also demonstrates the rising financial capacity of Chinese companies to invest in AI infrastructure. A 1 GW complex equipped with advanced accelerators, according to an estimate cited by Nvidia CEO Jensen Huang, could require about $50 billion in investment.
Despite the size of the project, data center costs vary depending on technology and location. AI-focused structures in China generally present lower values than equivalents installed in the United States.
