deepseek-ai /

DeepSeek-V4.1-Flash

105 DZD in 420 DZD out 2.4 DZD cached/ 1M tokens

DeepSeek V4.1 Flash is a multimodal Mixture-of-Experts model built around one goal: making the memory cost of long context collapse. It carries 552 billion backbone parameters but activates only 8 billion per token while reading your input and 16 billion while writing its answer — an asymmetry made possible by a causal encoder-decoder design where the decoder's key-value cache is projected from the encoder's final states rather than rebuilt layer by layer. The result is 890 bytes of cache per token, roughly a quarter of the previous generation and a fraction of a percent of where the series began. Reasoning effort is a continuous integer from 1 to 100 rather than a handful of preset levels, so cost and accuracy can be tuned rather than chosen from a menu.