Research
vLLM at 10K QPS: What 50-Engineer ML Teams Learned Scaling Open-Weight LLM Inference
Teams hitting 10K QPS on vLLM aren’t winning on hardware—they’re winning on operational rigor. The real cost isn’t the GPU bill. It’s the engineering time spent debugging KV-cache thrashing and speculative decoding edge cases no one saw in staging.