Multi-Stream LLMs: new paper on parallelizing/separating prompts, thinking, I/O

Multi-Stream LLMs (arXiv:2605.12460) proposes parallelizing prompt processing, chain-of-thought reasoning, and output generation across separate streams to reduce sequential bottlenecks in LLM inference. The method targets agentic workloads where latency and throughput are critical. If validated, this could reduce compute costs for complex reasoning tasks that current serial architectures handle inefficiently.