Disaggregated Inference Is an Operations Story Too, Not Just Tokens Per Second
ai · x · 2026-10-15
Key points
- Most AI inference discussions start with tokens per second and cost per token, but these metrics alone don't capture delivered performance.
- As inference architectures become heterogeneous (prefill/decode disaggregation), real-world performance increasingly depends on operational orchestration: scheduling across node types, load balancing, capacity planning, and monitoring.
- The article argues teams should treat disaggregated inference the way they treat large-scale service ops, not just as a benchmarks problem.
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