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DeepSeek-V4-Flash Update The official release of the DeepSeek-V4-Flash API is now in public beta. The API calling method remains unchanged — simply set the model name to deepseek-v4-flash to use the latest version. Significantly enhanced agent capabilities, with benchmark results far exceeding V4-Pro-Preview: Terminal Bench 2.1: 82.7 NL2Repo: 54.2 Cybergym: 76.7 DeepSWE: 54.4 Toolathlon verified: 70.3 Agent Last Exam: 25.2 Automation Bench (Public): 25.1 DSBench-FullStack: 68.7 DSBench-Hard: 59.6 Note 1: For the Code Agent tasks in the public benchmark sets, the official DeepSeek-V4-Flash was tested using the DeepSeek Harness minimal mode (to be released soon) as the framework, with the max effort level, topp=0.95, and temperature=1.0 Note 2: DSBench-FullStack is an internal full-stack development test set, and DSBench-Hard is an internal Coding Agent hard-problem test set The official V4-Flash natively supports the Responses API format and is specifically adapted for Codex. For the specific configuration, please refer to the documentation . DeepSeek-V4-Flash-0731 keeps the same model architecture and size as DeepSeek-V4-Flash-Preview, and was only re-post-trained. Note: This upd
Action requiredReview affected integrations and migrate before the documented retirement boundary.
DeepSeek-V4 The DeepSeek API now supports V4-Pro and V4-Flash, available via both the OpenAI ChatCompletions interface and the Anthropic interface. To access the new models, the base_url remains unchanged, and the model parameter should be set to deepseek-v4-pro or deepseek-v4-flash . The two legacy API model names, deepseek-chat and deepseek-reasoner , will be discontinued in three months (2026-07-24). During the current period, these two model names point to the non-thinking mode and thinking mode of deepseek-v4-flash , respectively. For more details, please refer to this documentation .
Action requiredReview affected integrations and migrate before the documented retirement boundary.
DeepSeek-V3.2-Exp Both deepseek-chat and deepseek-reasoner have been upgraded to DeepSeek-V3.2-Exp. deepseek-chat corresponds to DeepSeek-V3.2-Exp's non-thinking mode deepseek-reasoner corresponds to DeepSeek-V3.2-Exp's thinking mode For more details, please refer to this documentation .
API Launches Context Caching on Disk Technology The DeepSeek API has innovatively adopted hard disk caching, reducing prices by another order of magnitude. For more details on the update, please refer to the documentation Context Caching is Available 2024/08/02 .
deepseek-reasoner deepseek-reasoner is our new model DeepSeek-R1. You can invoke DeepSeek-V3 by specifying model='deepseek-reasoner' . For details, please refer to: DeepSeek-R1 Release For guides, please refer to: Thinking Mode
deepseek-chat The deepseek-chat model has been upgraded to DeepSeek-V2-0628. Model's reasoning capabilities have improved, as shown in relevant benchmarks: Coding: HumanEval Pass@1 79.88% -> 84.76% Mathematics: MATH ACC@1 55.02% -> 71.02% Reasoning: BBH 78.56% -> 83.40% In the Arena-Hard evaluation, the win rate against GPT-4-0314 increased from 41.6% to 68.3%. The model's role-playing capabilities have significantly enhanced, allowing it to act as different characters as requested during conversations.
deepseek-chat The deepseek-chat model has been upgraded to DeepSeek-V2-0517. The model has seen a significant improvement in following instructions, with the IFEval Benchmark Prompt-Level accuracy jumping from 63.9% to 77.6%. Additionally, on API end, we have optimized model ability to follow instruction filled in the ``system" part. This optimization has significantly elevated the user experience across a variety of tasks, including immersive translation, Retrieval-Augmented Generation (RAG), and more. The model's accuracy in outputting JSON format has been enhanced. In our internal test set, the JSON parsing rate increased from 78% to 85%. By introducing appropriate regular expressions, the JSON parsing rate was further improved to 97%. Previous DeepSeek API Upgrade Date: 2026-09-10 DeepSeek-V4.1-Flash Release Date: 2026-08-21 DeepSeek-V4-Flash-Vision-Exp Release Date: 2026-08-13 DeepSeek-V4-Pro Update Date: 2026-07-31 DeepSeek-V4-Flash Update Date: 2026-04-24 DeepSeek-V4 Date: 2025-12-01 DeepSeek-V3.2 DeepSeek-V3.2-Speciale Date: 2025-09-29 DeepSeek-V3.2-Exp Date: 2025-09-22 DeepSeek-V3.1-Terminus Date: 2025-08-21 DeepSeek-V3.1 Date: 2025-05-28 deepseek-reasoner Date: 2025-03-
DeepSeek-V4-Pro Update The GA release of DeepSeek-V4-Pro has been rolled out on the APP, Web, and API. The API calling method remains unchanged — simply set the model name to deepseek-v4-pro to use the latest version. Significantly enhanced Agent capabilities The GA version of DeepSeek V4 Pro greatly enhances agent capabilities, with particularly significant performance improvements in production environments. HLE (wo / w tools): 42.7/60.0 Terminal Bench 2.1: 87.9 NL2Repo: 61.5 Cybergym: 83.3 DeepSWE: 62.7 Toolathlon-Verified: 74.1 Agents' Last Exam: 25.7 AutomationBench (Public): 31.8 DSBench-FullStack: 71.1 DSBench-Hard: 67.2 Native support for the Responses API The DeepSeek API now natively supports the OpenAI Responses API format and is specifically adapted for Codex. Users can refer to the official documentation and complete the Codex configuration with a one-click configuration script. More flexible thinking effort control The thinking modes of V4-Pro and V4-Flash now support three thinking effort levels: low / high / max. In real-world usage, users can flexibly choose based on task complexity: use low for simple tasks, high for daily Agent tasks, and max for more complex s
DeepSeek-V3.1 Both deepseek-chat and deepseek-reasoner have been upgraded to DeepSeek-V3.1. deepseek-chat corresponds to DeepSeek-V3.1's non-thinking mode , while deepseek-reasoner corresponds to its thinking mode . Key updates in DeepSeek-V3.1: Hybrid reasoning architecture : A single model supports both thinking mode and non-thinking mode Improved reasoning efficiency : Compared to DeepSeek-R1-0528, DeepSeek-V3.1-Think provides answers in significantly less time Enhanced agent capabilities : With post-training optimization, the new model achieves major improvements in tool usage and intelligent agent tasks SWE-bench Verified: 66.0 SWE-bench Multilingual: 54.5 Terminal-bench: 31.3
deepseek-coder The deepseek-coder model has been upgraded to DeepSeek-Coder-V2-0614, significantly enhancing its coding capabilities. It has reached the level of GPT-4-Turbo-0409 in code generation, code understanding, code debugging, and code completion. Additionally, it possesses excellent mathematical and reasoning abilities, and its general capabilities are on par with DeepSeek-V2-0517.
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