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Any model. Any hardware. Zero compromise. Built with @ziglang / @openxla / MLIR / @bazelbuild

A retargetable MLIR-based machine learning compiler and runtime toolkit.

An MLIR-based compiler framework bridges DSLs (domain-specific languages) to DSAs (domain-specific architectures).

A native ahead-of-time (AOT) and JIT compiler for TypeScript, built on LLVM/MLIR. It compiles .ts files directly to native executables, WebAssembly, or runs them on the fly via a built-in JIT — no Node.js or JavaScript runtime required.

High-performance automatic differentiation of LLVM and MLIR.

Intel® Extension for MLIR. A staging ground for MLIR dialects and tools for Intel devices using the MLIR toolchain.

A close-to-metal Python API for programming AMD Ryzen™ AI NPUs (AI Engines), built on an open-source MLIR-based compiler toolchain.

Machine learning compiler based on MLIR for Sophgo TPU.

TPP experimentation on MLIR for linear algebra

DHLS (Dynamic High-Level Synthesis) compiler based on MLIR

Optimize Julia Functions With MLIR and XLA for High-Performance Execution on CPU, GPU, TPU and more.

MLIR-based partitioning system

CUDA Tile IR is an MLIR-based intermediate representation and compiler infrastructure for CUDA kernel optimization, focusing on tile-based computation patterns and optimizations targeting NVIDIA tensor core units.