DeepSeek ships V4.1-Flash-1017: higher coding and agent scores, shorter outputs, MIT weights and a Search API
On October 17, 2026 DeepSeek upgraded V4.1-Flash to V4.1-Flash-1017 across web, app and API, with the API calling method and pricing unchanged; it says the model scores higher, finishes faster and writes shorter outputs. Weights are on Hugging Face and ModelScope under MIT. DeepSeek also opened Search and Fetch APIs backed by its in-house search engine at $0.75 per 1,000 successful requests per endpoint.
DeepSeek’s API changelog for October 17, 2026 says DeepSeek V4.1 Flash has been upgraded to DeepSeek-V4.1-Flash-1017, and the official web and app models now use the new version too. API calling and pricing are unchanged: the model name deepseek-flash points to the latest model. DeepSeek calls it a performance–cost Pareto improvement, with shorter task runtime and output length, and says it optimized for DeepSeek Harness, Tencent CodeBuddy, WorkBuddy and other platforms, recommending DeepSeek Harness 0.2.1-rc.1 or later.
By DeepSeek’s own numbers, 1017 versus the previous V4.1-Flash moves Terminal-Bench 4.0 from 31.2 to 42.3, DeepSWE v1.1 from 74.2 to 77.0, ProgramBench from 20.3 to 29.1, Automation-Bench v1.0.6 from 54.8 to 60.5, and HLE without tools from 36.8 to 42.6 (44.0 on the text-only subset). Terminal-Bench 4.0 used the Claude Code harness and DeepSWE the Mini-SWE-V2 harness. In DeepSeek’s comparison table it leads the listed Claude Opus 5 and GPT 5.6-Sol on DeepSWE, Automation-Bench, Agents’ Last Exam and Apex Bench, but still trails Claude Opus 5 on HLE, Terminal-Bench 4.0, ProgramBench and NL2Repo-Bench. All figures are vendor-reported.
Weights are published on Hugging Face and ModelScope, with the repository and weights under the MIT License. The model card describes a minor update to V4.1-Flash at 763B parameters, recommending a 1M-token context window, max_tokens of at least 256K, and temperature and top_p of 1.0. The release ships no Jinja chat template; instead it includes a Python reference encoder (encoding.py) and deepseek-recipe, a toolkit that converts Messages, Chat Completions and Responses requests into DeepSeek V4/V4.1 prompt format.
The same day DeepSeek opened its in-house search engine to developers through a Search API, which returns structured web results for a query, and a Fetch API, which returns a single page as Markdown. Each is billed per successful request at $0.75 per 1,000; empty results, failures and timeouts are free, and each account gets 5 QPS per API. Server-side tool calls via DeepSeek Harness, Claude Code and Codex are free for now, with billing starting at 00:00 Beijing time on November 1, 2026 per the docs.
Sources
- DeepSeek-V4.1-Flash-1017: Wish-Driven Programming Made Real — DeepSeek
- Change Log | DeepSeek API Docs — DeepSeek
- deepseek-ai/DeepSeek-V4.1-Flash-1017 — DeepSeek (Hugging Face)
- Search & Fetch | DeepSeek API Docs — DeepSeek