Tiny CUDA Neural Networks is a lightweight framework for training and querying neural networks on GPUs. It provides fully-fused multi-layer perceptrons and multiresolution hash encodings optimized for speed, supporting various input encodings, loss functions like L2, and optimizers like Adam. The framework exposes a C++/CUDA API and offers optional JIT fusion for additional performance gains.