LLM context compression at 16x beats KV cache

LLM context compression at 16x beats KV cache

Context windows are becoming a computational bottleneck. The longer an agent runs, the more tokens accumulate from retrieved documents, reasoning traces and conversation history, and the more memory and compute that growing context demands. Most existing solutions either degrade model accuracy, require the full context to load before compression begins, or produce memory savings that don't translate into real speedups in standard serving infrast…