A minor incident recently occurred in the AI community: On October 20, DeepSeek officially announced the full open-sourcing of its internal inference framework, DeepInfer. While the focus should have been on technical insights, a blunder on the official account's article cover—where 'inclusive' was miswritten as 'HP'—sparked heated discussions among netizens. This framework integrates high-performance operators and a deeply optimized inference engine, supporting capabilities such as distributed inference and speculative decoding, and is compatible with NVIDIA and Huawei Ascend platforms. DeepSeek stated that by open-sourcing its internal deployment experience, it aims to help developers and enterprises optimize throughput and latency for large-scale inference, efficiently build private and public cloud deployments, reduce computing costs, minimize energy consumption, and make intelligence more accessible to a broader audience at lower prices, thereby achieving large-scale model inclusivity. Currently, DeepInfer has enabled high-throughput, low-latency large-scale inference services for DeepSeek V4.1 Flash, with a single cluster service throughput reaching 155 trillion Tokens/day. In the future, the inference code for DeepSeek's new models and subsequent optimizations will also be continuously updated here. Additionally, DeepSeek has simultaneously open-sourced the production-grade token encoding and decoding component, deepseek-recipe, ensuring the community receives an API experience consistent with the official deployment. The cover text error has been urgently corrected, with technical insights remaining the focal point.