Public model comparisons often compress a complex decision into a single rank. That is useful for orientation and dangerous for selection. Enterprise workloads impose different requirements: some reward response quality above all else; others are dominated by latency, unit economics, deployment control, data boundaries or predictable structured output.
A practical evaluation frame
ZContinuum treats model selection as a weighted decision across dimensions that can be observed and challenged. The minimum useful frame includes task quality, latency, cost, context behaviour, structured-output reliability, control, privacy constraints and operational fit.
The question is not “Which model is best?” It is “Which model is best for this workload, under these constraints, with these consequences?”
Separate measurement from judgement
Measurements should remain measurements: latency in milliseconds, cost per unit of work, accuracy on a defined test set, failure rate under a specified schema. Judgement enters when the organisation decides how much each dimension matters. Mixing the two makes evaluation difficult to audit.
What comes next
The next research stage is to define workload-specific test packs, version the prompts and datasets, capture repeated runs, record cost and latency, and publish both the result and the limitations. A benchmark without provenance is marketing. A benchmark with provenance can become engineering evidence.