DeepInfer

DeepInfer is DeepSeek's public high-performance inference framework, and its README describes it as the framework that "powers DeepSeek's large-scale production services." It supports offline inference of the DeepSeek-V4.1-Flash model on NVIDIA GPUs and Huawei Ascend NPUs. Inference runs on your own machines or cluster, and the examples show no step that sends your prompts back to DeepSeek's online service. It's a framework you build and deploy yourself, not a hosted service.

Who it's for:Engineers responsible for model deployment and inference infrastructure. Readers who don't write code won't have a use for it.

Before you start: Following the README, you clone the repository, prepare the environment and run build.sh, which needs NVIDIA or Ascend driver dependencies and build tools. build.sh installs the matching requirements; on the NVIDIA path it force-replaces the NCCL package and compiles components such as FlashMLA, DeepEP and DeepGEMM locally before installing them, so a dedicated environment is a good idea. Models load from a Hugging Face identifier or a local checkpoint, and model weights have their own terms. No paid API account is needed; you supply the GPUs or cloud compute. The code is Apache-2.0 licensed.

Based on the project's public documentation. Not tested by AI Inspiration World.