UltraQuant: 4-bit KV Caching for Context-Heavy Agents

Language model agents that maintain long, multi-turn conversations place enormous pressure on GPU memory, primarily because the key-value cache — a stored record of prior context — grows with every exchange. At scale, this becomes a bottleneck that throttles how many users a system can serve simultaneously. UltraQuant attacks this problem with aggressive 4-bit compression of the KV cache, achieving over three times faster time-to-first-token in late conversation rounds without meaningful quality loss. The practical implications are significant for any organization running high-concurrency agent deployments, including customer service platforms, coding assistants, and long-context document analysis tools.