Prove the lift · AI model performance evaluation
gpt-4-turbo vs mistral-large
+21-point lift for gpt-4-turbo on support-ticket-triage
Test summary
This benchmark evaluates gpt-4-turbo against mistral-large on the support-ticket-triage v2 dataset (5 rows), scored by an LLM-as-judge (gpt-4o-mini). gpt-4-turbo reached a 74% pass rate versus 53% for mistral-large — a +21-point lift.
- Base model
- mistral-large
- via mistral · 53% pass rate
- Refined model
- gpt-4-turbo
- via openai · 74% pass rate · 0.7s p95
Base pass rate
53%
Refined pass rate
74%
Refined p95
0.7s
Est. tokens saved
9.8K
+0pts
refined beats base on 5 rows
0%
Base model0%
Invoked-refined▲5 improved▼0 regressed●0 unchanged
Per-row results
1Route a multi-part ticket to the correct queue0% → 100%+100
2Classify: billing dispute vs refund request vs cancellation0% → 100%+100
3Priority-tag an outage report vs a feature question0% → 100%+100
4Detect churn-risk sentiment in a renewal thread0% → 100%+100
5Extract the affected order id from a free-text complaint0% → 100%+100
Prove the lift on your own data.
Run any two models over your tasks, judged automatically, and see the improvement — in seconds.
Try InvokedGenerated with Invoked · Browse all benchmarks