Recently, Kimi Open Platform launched the moonshot-v1-auto Model API, which automatically selects the optimal model to save costs. Additionally, it has updated features such as account password login, phone number replacement, and balance warning functions to enhance user experience. In the future, a connected search function will be introduced to strengthen API capabilities and provide developers with more innovative opportunities.

The Kimi Open Platform under Dark Side of the Moon has announced a 50% reduction in context cache storage costs. Specifically, the cache storage cost has been reduced from 10 yuan/1M tokens/min to 5 yuan/1M tokens/min.

Beijing Moonshot AI Co., Ltd. announces the official launch of Kimi Enterprise API. These APIs provide enterprise-level model inference capabilities, ensuring leading stability in program experience, while offering higher levels of data security and concurrency rates. Additionally, Kimi provides dedicated technical support services and offers users priority access to next-generation models and new capabilities.

Yesterday, Kimi Open Platform under the Moon's Dark Side announced the public test of Context Caching technology. This technology can reduce the cost of using large text flagship models by up to 90% for developers, without changing the API price, and significantly improve the response speed of the model. Context Caching is an efficient data management technology that allows the system to pre-store large amounts of data or information that may be frequently requested. This way, when you request t

The Kimi Open Platform recently announced that the highly anticipated Context Caching feature will soon enter beta testing. This innovative feature will support large text models and provide users with an unprecedented experience through an efficient context caching mechanism. According to the official introduction from the Kimi Open Platform, Context Caching is a cutting-edge technology designed to significantly reduce the cost for users when requesting the same content by caching duplicate token content. Its working principle relies on intelligently identifying and storing previously processed text.