oLLM is a lightweight Python library designed for large-context LLM inference, allowing users to run substantial models on consumer-grade GPUs without quantization. The latest update includes support for various models, improved VRAM management, and additional features like AutoInference and multimodal capabilities, making it suitable for tasks involving large datasets and complex processing.

A new compiler called Mirage Persistent Kernel (MPK) transforms large language model (LLM) inference into a single, high-performance megakernel, significantly reducing latency by 1.2-6.7 times. By fusing computation and communication across multiple GPUs, MPK maximizes hardware utilization and enables efficient execution without the overhead of multiple kernel launches. The compiler is designed to be user-friendly, requiring minimal input to compile LLMs into optimized megakernels.