ByteIR provides compiler, runtime, and frontend components for end-to-end model compilation. It adopts upstream MLIR dialects and Google MHLO to lower state-of-the-art deep learning models and supports PyTorch, TensorFlow, and ONNX frontends. The project enables DL ASIC compilers to leverage generic graph, loop, and tensor-level optimizations while focusing on backend-specific code generation.