Modal details how to serve trillion-parameter coding agents at trillion-token scale

Modal 详解如何以万亿 token 规模服务 Kimi K2.6 编码 Agent 推理

Modal's engineering team published a deep-dive on serving Moonshot AI's Kimi K2.6 for coding agents. They boosted per-replica performance by 2.8x per user and 5.6x across users, turning a ruinously expensive service into a price-competitive one. One service processed hundreds of billions of tokens per day and trillions in aggregate. The post walks through workload analysis for hybrid-attention MoE models and the engineering optimizations applied. Exact GPU models and per-request latency numbers are not disclosed in the body.

Why it matters: Modal's engineering breakdown of inference acceleration for Moonshot AI's Kimi K2.6 delivers two hard numbers — 2.8x and 5.6x speedups — directly useful for inference engineers. Not scored higher because this is infra optimization, not a model capability or product update; aud...