Tools/NVlabs/cuda-oxide

cuda-oxide

cuda-oxide is an experimental Rust-to-CUDA compiler that lets you write (SIMT) GPU kernels in safe(ish), idiomatic Rust. It compiles standard Rust code directly to PTX — no DSLs, no foreign language bindings, just Rust.

3.0k+35/wkemergingRustApache License 2.0trending

The Lens

By Erik Loyd, SaaS CEO and former COO/CFO of an AWS Premier Partner.

Updated Jun 2026

cuda-oxide lets you write GPU code in plain Rust and compiles it straight to CUDA. Normally, programming an NVIDIA GPU means CUDA C or C++ or a special DSL, this NVIDIA Labs project compiles standard Rust down to PTX, the low-level bytecode the GPU actually runs. You get generics, closures, GPU intrinsics, even async, in a language with real memory safety.

There's nothing to host, it's a compiler toolchain you install and build against. The ops burden is the real story: this is low-level GPU work, so you need an NVIDIA GPU, the CUDA toolkit, and the patience to deal with an early compiler. It is not a smooth on-ramp, it's a power tool for people who already know what PTX is.

Rust developers doing GPU compute who don't want to drop into C++ are the audience. If you're happy in CUDA C or using higher-level ML frameworks that hide the GPU entirely, you don't need this. The appeal is writing kernels in one safe language instead of context-switching into C++ every time you touch the hardware.

The catch: it's explicitly early-alpha. NVIDIA's own README warns of bugs, missing features, and breaking API changes. It's free and Apache-licensed and the idea is excellent, but this is a watch-and-experiment project, not something to put under production kernels yet. Treat it as a preview of where Rust-on-GPU is heading.

Free vs Self-Hosted vs Paid

fully free

Free tier: Free and open source under Apache-2.0 (dual-licensed with NVIDIA's software license). No paid version.

Self-hosted: A compiler toolchain you install locally. Free. You need NVIDIA hardware and the CUDA toolkit.

Paid: None.

Free and open source (Apache-2.0), early-alpha. Needs NVIDIA hardware to use.

Self-hosting ops:significant

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Score
80/100 · A
Adoption17/30
Maintenance25/25
Community13/20
License15/15
Analysis10/10

A low score is not a verdict on quality. Young and niche tools start low by design. How we calculate scores

Trust Signals

Community discussions enabledOrganization account (482 public repos)Notable author: 10,534 followersAuthor also built: NVlabs/GatedDeltaNet-2 (209 stars)

License: Apache License 2.0

Use freely. Patent grant included.

Commercial use: ✓ Yes

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