News Summary

• DeepSeek-V4.1-Flash delivers substantial improvements across reasoning, coding, agentic tasks, and visual benchmarks.
• The model reduces task execution time and output length, enabling users to complete tasks faster and at lower cost.
• The encoding folder contains a self-contained Python reference implementation with test cases for multi-turn conversations, tool calling, thinking mode, numeric reasoning effort, mid-conversation system messages, and interleaved image content.
• For production use, we additionally release deepseek-recipe, a set of Rust libraries with Python bindings that provides the same prompt format as a protocol-aware toolkit.