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US Department of Homeland Security bans federal civilian agencies from using DeepSeek and related products

The US Department of Homeland Security publicly issued a ban on October 19, requiring US federal civilian executive agencies to stop procuring DeepSeek-related products and services and to remove DeepSeek-related products from existing information technology systems, including third-party products and services developed using DeepSeek solutions. According to the US Cybersecurity and Infrastructure Security Agency list, federal civilian executive agencies include 102 agencies such as the Department of the Treasury, the Department of Justice, the Department of State, and the Department of Agriculture. DeepSeek had previously been banned by the US Department of Commerce, congressional offices, the Pentagon, NASA, the US Navy and other departments; this time the ban has been expanded to all US federal civilian agencies.

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US Department of Homeland Security bans civilian government agencies from using DeepSeek

The US Department of Homeland Security has ordered the removal of DeepSeek-related technology from most government systems, prohibiting civilian government agencies from using DeepSeek and any technology built with its models; the ban takes effect at the end of July, and agencies under the Department of Defense are not included. The report notes that DeepSeek said last year that training the initial version of its model cost about $6 million, while OpenAI's GPT-4-related costs were about $100 million, and that US companies such as Snowflake, Vercel, and OpenRouter have also integrated DeepSeek into their products.

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DeepSeek Completes Nearly 100 Billion Yuan Financing at a Pre-Money Valuation of 500 Billion Yuan

DeepSeek's new financing round has closed, with fundraising guaranteed at 80 billion yuan and ultimately expected to approach 100 billion yuan, while the pre-money valuation remains at 500 billion yuan; founder Liang Wenfeng personally contributed about 20 billion yuan. In the first seven months of 2026, the company's revenue was 475 million yuan, with a net loss of 715 million yuan, and the API business gross margin was 82.9%. The funds are mainly directed toward a GW-level intelligent computing center in Ulanqab, Inner Mongolia, where the company plans to deploy 160,000 Huawei Ascend 950DT chips; the company plans to submit a prospectus by the end of 2026 and list on the STAR Market in 2027.

DeepSeek-V4.1-Flash-1017 Tops Code Arena WebDev Open-Source Leaderboard

Arena announced that DeepSeek-V4.1-Flash-1017 (Max) surpassed open-source models such as Kimi K3 (Max) with a score of 1670, becoming the highest-ranked open-source model on the Code Arena: WebDev leaderboard, and also surpassed closed-source models such as Claude Opus 5 and Grok 4.7, trailing GPT-6 Sol by only 12 points. The model was launched on October 17, priced at 2 yuan per million tokens for input (cache miss) and 8 yuan for output during peak hours, and 1 yuan for input and 4 yuan for output during idle hours, with a comprehensive cost of about 1/10 that of Kimi K3. Zhidongxi used it to create two cases, an ancient Kaifeng 3D scene and a web-based racing game, both completed in a single attempt, at a total cost of about 6 yuan.

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DeepSeek Opens Up Search and Fetch Search APIs, Charging $0.75 per Thousand Requests

DeepSeek is opening its in-house search engine to external developers through two new APIs, Search and Fetch, which can retrieve real-time web search results and webpage body text. It charges $0.75 per 1,000 successful requests, requires no additional model calls, and can be used in applications powered by other vendors' models. Search returns ranked results with titles, URLs, snippets, and summaries, while Fetch returns the content of a single webpage in Markdown format; the company says the engine handles hundreds of millions of requests per day and its index contains hundreds of billions of webpages. The release coincides with a minor version update, DeepSeek-V4.1-Flash-1017. The API documentation shows that each account is limited to 5 Search and 5 Fetch requests per second, a single search returns at most 50 results, and only requests that return results are billed.

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DeepSeek-V4.1-Flash-20261017 Tops the Code Arena WebDev Open-Source Model Leaderboard

Arena says DeepSeek-V4.1-Flash-20261017 (Max) has become the top-ranked open-source model on the Code Arena WebDev leaderboard, surpassing Kimi K3 (Max) at 10 times lower cost. The model ranks 12th overall with 1,670 points, above Claude Opus 5 (High) and about 10 points behind GPT-6 Sol (Max); it is priced at $0.3/$1.2 per million input/output tokens, a 52-point improvement over the previous version DeepSeek-V4.1-Flash-20260910.

Codex Chinese Version + DeepSeek-V4.1-Flash-1017: Generate a Four-Quadrant Sticky Note App from a Single Sentence and Upload It to GitHub

The author used the Chinese-localized version of Codex, DeepSeek-V4.1-Flash-1017, and the Hermes agent to generate a four-quadrant sticky note app from a single prompt and automatically upload and publish it to GitHub. The finished product supports Chinese and English, a time capsule, free resizing of sticky notes, and local saving, and is packaged as a single-file portable app; the first version generated a static index.html in about six or seven minutes, and later iterations changed it to a sticky-note format. The whole process cost a little over four yuan.