When comparing paid tiers of a credit-metered AI generation platform, convert each plan's raw credit allotment into a concrete count of completed real workflows per month rather than comparing credit totals or subscription price directly. Different output types can cost wildly different credit amounts (e.g., a video generation costing roughly 13x more credits than a single image), so a plan's credit number in isolation is misleading — a tier that looks generous may support only a couple of full end-to-end workflow runs per month.
To apply: define a fixed representative workflow (the actual assets and steps you intend to produce), price it once in the platform's credit units, then divide each tier's monthly credit allotment by that price to get "runs per month" as the real basis for comparison.
This approach also exposes when a tier's limitation is really a throttled credit ceiling rather than a locked-out feature — a premium model can be nominally available on every tier while only being practically usable at higher tiers, since a low tier's total credits may not cover even a handful of runs that use it.
Example: on Higgsfield, Starter/Plus/Ultra/Business tiers all technically expose the same generation models, but Starter's 200 credits cover only 2 runs of a 97-credit image+video workflow, while Ultra's higher sub-tiers cover up to ~92 runs. Value per credit generally improves as spend increases toward the top tier — though shared/team tiers (like Business) can trade a worse per-credit rate for a shared credit pool and workspace instead, a different value axis than raw output volume.