Prove the lift · AI model performance evaluation
gpt-4-turbo vs mistral-large
-9-point lift for gpt-4-turbo on insurance-extraction-eval
Test summary
This benchmark evaluates gpt-4-turbo against mistral-large on the insurance-extraction-eval v1 dataset (7 rows), scored by an LLM-as-judge (llama-3.1-8b). gpt-4-turbo reached a 32% pass rate versus 41% for mistral-large — a -9-point lift.
- Base model
- mistral-large
- via mistral · 41% pass rate
- Refined model
- gpt-4-turbo
- via openai · 32% pass rate · 1.9s p95
Base pass rate
41%
Refined pass rate
32%
Refined p95
1.9s
Est. tokens saved
267
−0pts
no lift — the base model held its ground
0%
Base model0%
Invoked-refined▲2 improved▼0 regressed●5 unchanged
Per-row results
1Subrogation waiver interaction with additional-insured status100% → 100%0
2Coinsurance 80% clause recovery on an under-insured building100% → 100%0
3Business-interruption period-of-restoration calculation0% → 0%0
4Suit-limitation clause: is a late-filed claim contractually barred?0% → 100%+100
5Replacement cost vs ACV on a depreciated roof0% → 0%0
6Aggregate deductible across a loss sequence under a per-occurrence + annual cap0% → 0%0
7Named-peril coverage determination under a basic HO form0% → 100%+100
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