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AI Model Evaluation Scorecard Template
A structured scorecard for evaluating LLM and ML model performance across accuracy, latency, cost, safety, and user satisfaction metrics before and...
Updated 2026-03-04
AI Model Evaluation Scorecard
| # | Item | Value (1-10) | Effort (1-10) | Score | Priority | Owner | |
|---|---|---|---|---|---|---|---|
| 1 | 3.0 | ||||||
| 2 | 2.5 | ||||||
| 3 | 1.8 | ||||||
| 4 | 1.2 | ||||||
| 5 | 1.1 |
#1
3.0
#2
2.5
#3
1.8
#4
1.2
#5
1.1
Edit the values above to try it with your own data. Your changes are saved locally.
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Frequently Asked Questions
How many test cases do I need for a reliable evaluation?+
Minimum 50 representative examples plus 10-15 adversarial cases. For high-stakes applications (medical, legal, financial), aim for 200+ examples covering every category of input your product handles. The key is coverage of your input distribution, not raw volume.
Should I weight all dimensions equally?+
No. Dimension weights should reflect your product's specific constraints. A real-time chatbot should weight latency at 25-30%. A batch processing pipeline can weight latency at 5% and put more weight on cost and accuracy. Discuss weights with your team before scoring begins.
How often should I re-run the evaluation?+
Re-evaluate quarterly, when a major new model version launches, or when your production metrics show drift from baseline scores. Set automated alerts for [token cost per interaction](/metrics/token-cost-per-interaction) and accuracy metrics to trigger ad-hoc re-evaluations.
Can I use this scorecard for traditional ML models, not just LLMs?+
Yes. Replace the LLM-specific criteria (hallucination rate, token costs, context window) with ML-appropriate metrics (precision, recall, F1 score, inference time, training cost). The weighted scorecard structure works for any model comparison.
Who should participate in the evaluation?+
At minimum: the PM (owns weights and final decision), the ML engineer (owns scoring methodology and test harness), and a domain expert (validates output quality). For safety-critical products, add a representative from legal or compliance.
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