DeepSeek V4.1 Flash (Non-reasoning)

DeepSeek-V4.1-Flash is a multimodal Mixture-of-Experts (MoE) language model developed by DeepSeek, built on a novel Causal Encoder–Decoder architecture. Featuring a total backbone size of 552B parameters, the model uses an asymmetric design that activates 8 billion parameters during prefill and 16 billion parameters during decoding to achieve high throughput and low latency. It provides native support for visual understanding alongside text processing and features a context window of up to one million tokens.

Designed for agentic applications, long-context analysis, and complex coding workflows, the model supports a continuously controllable reasoning effort ranging from 1 to 100. This sliding scale allows users to dynamically fine-tune the compute-accuracy tradeoff depending on the task complexity—ranging from basic classification and routing to advanced planning, debugging, and multi-step tool use. Its compressed KV cache design significantly lowers memory footprints and hosting overhead in large-scale production environments.