DeepSeek-V4-Flash正式版API开启公测
DeepSeek官方于2026年7月31日宣布,DeepSeek-V4-Flash正式版API进入公开测试。调用方式保持不变,模型名仍为deepseek-v4-flash;该版本在预览版基础上进行了后训练,强化智能体能力,原生支持Responses API并适配Codex。官方同时说明,本次只更新Flash API,V4-Pro API以及网页、App模型不变。
证据来源
查看来源摘录
Date: 2026-07-31 (https://api-docs.deepseek.com/updates/#date-2026-07-31) DeepSeek-V4-Flash Update (https://api-docs.deepseek.com/updates/#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 (https://api-docs.deepseek.com/quick_start/agent_integrations/codex) . DeepSeek-V4-Flash-0731 keeps the same model architecture and size as DeepSeek-V4-Flash-Preview, and was only re-post-trained. Note: This update only upgrades the DeepSeek-V4-Flash API. The DeepSeek-V4-Pro API and the APP/WEB models are unchanged. The official release of DeepSeek-V4-Pro will follow soon.
来自 星盘大模型百科