Flash Linear Attention provides optimized implementations of token-mixing layers including linear attention, sparse attention, and state space models. It supports hybrid LLM architectures like Mamba, Gated DeltaNet, MoBA, and YOCO, with platform-agnostic kernels verified on NVIDIA, AMD, and Intel hardware. The library includes fused modules, training utilities, generation helpers, and benchmarking tools.