Real-time LLM Inference on Standard GPUs: 3k tokens/s per request

The article demonstrates that standard datacenter GPUs can achieve 3,000 tokens/second for single-request LLM inference—comparable to specialized inference hardware—by co-optimizing the model architecture, runtime, and GPU kernels as a unified pipeline. For AI agents that require sequential decision-making loops, single-request decode speed is now the critical bottleneck rather than aggregate throughput, making 3,000 tokens/second transformative for real-time agent performance. The key insight is that decode speed is primarily limited by memory bandwidth, not compute power, meaning existing GPUs have untapped potential that current inference software stacks fail to expose.