DeepSeek just open-sourced its inference engine (github.com)

DeepSeek has announced the open-source release of its high-performance inference engine, DeepInfer, designed to enhance the scalability and efficiency of AI model deployment. This framework enables offline inference and incorporates essential features for serving large-scale AI applications. It supports various advanced models, including DeepSeek-V4.1-Flash, and introduces optimizations such as asynchronous scheduling, deterministic sampling, and structured outputs, which are crucial for maintaining performance across diverse workloads. The significance of DeepInfer lies in its comprehensive set of technical capabilities, which include optimized kernels, parallelism techniques like Attention DP and MoE EP, and batch-invariant inference that guarantees consistent results regardless of the input batch composition. This framework also integrates confidence-scheduled verification for improved decoding efficiency and operates seamlessly on NVIDIA and Huawei hardware. With its Apache License 2.0 release, DeepInfer not only democratizes access to cutting-edge AI inference technologies but also provides a valuable resource for the AI/ML community to build and deploy scalable applications efficiently.