DeepSeek released DeepSeek-V4.1-Flash and says it beats its larger DeepSeek-V4-Pro on performance, cost, speed, and total runtime. Starting Sept. 14, V4-Pro API requests will be served by V4.1-Flash and billed at Flash’s rates until V4.1-Pro launches, while V4-Flash and the August experimental vision model are retired. The change shifts default routing and pricing to the smaller mixture-of-experts model, with V4-Pro becoming a temporary backend rather than the billed endpoint.
French investors via a pooled SPV bought into Moonshot AI, the China-based company behind the Kimi model family, ahead of its planned Hong Kong listing. The SPV put about €10 million into the last financing round, valuing Moonshot AI at a $30 billion pre-money level. This shifts capital toward open-weight model hosting in Europe and supports efforts to self-deploy Moonshot’s Kimi models with privacy-focused technologies.
DeepSeek AI released DeepSeek-V4.1-Flash, a multimodal Mixture-of-Experts model designed to reduce long-context KV-cache strain in LLM serving. The global KV cache footprint is 890 bytes per token with a 1M-token context window, and the model ships as open weights under an MIT license. Persistent KV caching is reduced (including FP4 quantization and bounded replay), enabling longer contexts to be more deployable with lower storage and bandwidth demands.
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