InfiniteHiP introduces a framework that dramatically extends LLM context processing while reducing computational demands.

• Dynamically eliminates irrelevant context tokens during inference
• Achieves up to 70% speedup in processing long contexts
• Maintains performance quality while handling contexts up to 3 million tokens
• Works with existing pre-trained models without requiring retraining

This engineering breakthrough makes long-context LLM applications more practical and accessible, enabling efficient document processing, complex reasoning, and knowledge-intensive applications on standard hardware.

InfiniteHiP: Extending Language Model Context Up to 3 Million Tokens on a Single GPU