Mushitags

 Concept illustration generated for this post; it does not depict the model or an actual product interface. DeepSeek released V4.1 Flash-1017 on October 17 and opened its Search and Fetch APIs to developers. Search returns structured web results; Fetch retrieves a page and returns its content as Markdown, giving agents and retrieval systems a way to access live web material. DeepSeek charges $0.75 per 1,000 successful requests to each endpoint. Calls made through DeepSeek Harness, Claude Code or Codex are currently free for DeepSeek API users, with billing scheduled to begin at 00:00 Beijing time on November 1 (16:00 UTC on October 31), according to the [API guide](https://api-docs.deepseek.com/guides/search/). The updated model is available through the existing `deepseek-flash` API name, and DeepSeek says the API method and pricing remain unchanged. The company describes the update as improving reasoning, coding, agent tasks and visual benchmarks while shortening task time and output length. Its [published model card](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017) shows gains over the previous Flash version on several tests, but results vary across benchmarks and are vendor-reported rather than independent evaluations. DeepSeek has also released the weights under the MIT license. The [Hugging Face repository](https://huggingface.co/deepseek-ai/DeepSeek-V4.1-Flash-1017) lists 763 billion parameters and instructions for serving the model with tools such as vLLM and SGLang. That makes it an open-weight release, but not a lightweight model for an ordinary laptop; practical local use requires substantial compute and storage. The update gives developers both a refreshed model and a new web-search option with per-request billing. The next useful comparison will be independent testing of quality, latency and total cost across real workloads. ~ai ~deepseek ~open_source