Guide
Designing a fair single model versus specialist workflow evaluation
Give the baseline the same material, a competent prompt and a comparable budget, score blind against a fixed answer key, and report losses alongside wins.
For evaluation and ml engineers. Written by the Encevra engine team. Reviewed 2026-10-12.
Equal inputs, equal budget
The baseline should receive the same source material and a prompt a capable engineer would write. Compare at matched cost when making efficiency claims; a workflow that spends four times more should be compared with a baseline allowed to spend more too.
Fix the scorer first
Write the answer key and scoring rules before running either system. Penalise explicit wrong answers, not just missing ones, and do not reward number-only matches.
Report everything
Publish sample count, cost, latency, failures and the cases where the baseline won. Encevra has not yet published a scored comparison for the engine catalog.
A minimal protocol
Run both systems on the same frozen task set, hide which system produced each answer from the scorer, and record every run including failures.
- Freeze tasks, answer key and scoring rules
- Run the baseline and the workflow at a recorded budget
- Score blind
- Publish wins, losses, cost and latency together
Frequently asked questions
- Has Encevra published a scored comparison?
- Not yet for the engine catalog.
- What budget should the baseline get?
- A comparable one. If the workflow spends more, allow the baseline more too when judging efficiency.
- Can I reuse public benchmarks?
- Use them for context, but decide on tasks from your own work.