In September 2026, NVIDIA announced it is leaning into native GPU programming in Rust. CUDA C++ and CUDA Python are mature, enterprise-grade toolchains, and NVIDIA will be growing and maturing CUDA Rust into 2027 and beyond. The systems layer of AI spans inference engines, serving infrastructure, drivers, and agent runtimes, and it churns constantly. More and more of it is written in Rust. NVIDIA is part of that shift. The Nova Linux driver is written in Rust. NVIDIA Dynamo is built on a Rust core. NVTX has Rust bindings.

The GPU kernel is the exception. You can launch kernels from Rust, but the kernel itself often has to be written in another language. NVIDIA CUDA Rust closes that gap. GPU kernels can be written in Rust, compiled natively to PTX, rather than a wrapper around code from somewhere else.

There are two tracks to use Rust, matching the two tracks CUDA itself has. SIMT is the model you already write in CUDA C++ or numba-cuda. Tile is a newer programming model, also available in C++ and Python. When you are picking one to build on, reach for Tile first. The compiler decides how tiles map onto each architecture, so your source doesn’t encode architecture-specific choices, and you drop to SIMT when you need that control.

Below is the same kernel on each track, which performs elementwise addition over 1,024 floats. The SIMT track: cuda-oxide is a custom rustc codegen backend. It intercepts compilation, routes #[kernel] functions through Rust MIR, the community Pliron IR framework, and LLVM IR down to PTX.