Qualify Cheaper Models Without Guesswork
Run automated baseline-versus-challenger evaluations against your objective success criteria. See where the challenger passes, fails, or needs fallback coverage — before you switch.
Get StartedWhy Choose ProofMap
Compare quality and cost
Evaluate your challenger runtime side-by-side with the current production baseline. Every criterion is scored — no guesswork, no cherry-picked demos.
See pass, fail, or fallback
The system surfaces where the challenger matches the baseline, where it falls short, and where a fallback mapping bridges the gap.
Promote only qualified mappings
Only prompt revisions that pass qualification can be promoted into an approved prompt package. Risky swaps never reach production.
Comparison
| Decision point | Manual evaluation | ProofMap |
|---|---|---|
| Compare baseline to challenger | Manually run both models, track results in a spreadsheet, guess at statistical significance. | Automated evaluation runs compare every criterion in parallel. Evidence links back to run reports. |
| Decide whether to switch | Debate in Slack or a meeting. No shared evidence. | Clear recommendation: Switch / Stay / Fallback — backed by pass-rate data, cost delta, and rationale. |
| Create fallback mapping for partial qualification | Manually route tasks to different models. No audit trail. | System creates a target-specific fallback mapping. Failing criteria route to the baseline; passing criteria use the cheaper challenger. |
| Justify staying on the current runtime | "It works." No data to defend the cost. | Qualification report shows exactly which criteria the challenger fails, producing evidence to justify the decision and avoid sunk-cost bias. |
Frequently Asked Questions
How do I test a cheaper model without risking production quality?
Define a success objective and run evaluations that compare the challenger runtime against your current baseline. ProofMap runs these evaluations in isolation — your production runtime is never affected. You see a full pass/fail matrix and a recommendation before you decide to switch.
What if the cheaper model only works for some runtimes or tasks?
Partial qualification is a first-class outcome. When a challenger passes some criteria but fails others, ProofMap recommends a fallback mapping: use the cheaper model for passing criteria and retain the baseline for the ones that need it. You get cost savings with zero quality regression.
Can the system justify staying on the more expensive model?
Yes. When a challenger fails critical guardrails, the qualification report produces evidence-backed rationale for staying on the baseline. This helps teams defend infrastructure spend with data rather than anecdotes.
Do I need to rewrite the prompt for every model?
Not necessarily. ProofMap supports prompt regression testing across target runtimes. If the challenger passes with your existing prompt, you can promote it directly. If it fails, the system helps you understand whether a prompt revision — or a runtime-specific override — can close the gap.
Start qualifying prompts
Run your first baseline-vs-challenger evaluation and see whether a cheaper runtime can safely reduce your model costs.
Start qualifying prompts