SLAM-LLM is an open-source deep learning framework designed to train customized Multimodal Large Language Models (MLLMs), with a focus on speech, language, audio, and music processing. It provides a modular configuration, detailed training and inference recipes, and high-performance checkpoints for mainstream tasks, aiming to accelerate research in audio-language models.