InternLM-XComposer-2.5 is a multifunctional large visual language model that supports long context input and output. It excels in various text-image understanding and generation applications, achieving performance comparable to GPT-4V while utilizing only 7B parameters for its LLM backend. Trained on 24K interleaved image-text context, the model seamlessly scales to 96K long context through RoPE extrapolation. This long context capability makes it particularly adept at tasks requiring extensive input and output context. Furthermore, it supports ultra-high resolution understanding, fine-grained video understanding, multi-turn multi-image dialogue, web page creation, and writing high-quality text-image articles.