How Modal serves trillions of tokens for trillion-parameter coding agents

Modal explains how it optimized Kimi K2.6 inference for coding agents, reaching 2.8x per-user and 5.6x cross-user performance per replica and running services at hundreds of billions of tokens per day. The work combines custom DFlash speculative decoding fine-tuned on coding traces, FP8 KV cache and NVFP4 shared-expert quantization, HiCache CPU-tier caching, and KV cache-aware load-based routing. Modal upstreamed its SGLang patches and released the configuration behind Modal Auto Endpoints.