DeepSeek-OCR's paper is titled Contexts Optical Compression -- OCR is just the means; what it actually validates is that 'rendering text as images and feeding them to a VLM' achieves 10x compression at 97% accuracy. This is a qualitative shift for long-context LLM and RAG token costs.
Kimi is a large language model from Chinese AI startup Moonshot AI, known for its ultra-long context window, open-source strategy, and highly competitive pricing. From 200K context in 2023 to K2.5 Agent Swarm in 2026, Kimi has become a force that the global AI market cannot ignore.
Traditional RAG splits documents into small chunks for retrieval, but this causes information fragmentation. LongRAG leverages 100K+ token long-context models to retrieve larger document segments (entire sections or even whole documents), reducing fragmentation while maintaining retrieval efficiency.