Prove the lift · AI model performance evaluation
claude-sonnet-4-6 vs llama-3.1-8b
-5-point lift for claude-sonnet-4-6 on insurance-extraction-eval
Test summary
This benchmark evaluates claude-sonnet-4-6 against llama-3.1-8b on the insurance-extraction-eval v1 dataset (8 rows), scored by an LLM-as-judge (claude-haiku-4-5). claude-sonnet-4-6 reached a 28% pass rate versus 33% for llama-3.1-8b — a -5-point lift.
- Base model
- llama-3.1-8b
- via ollama · 33% pass rate
- Refined model
- claude-sonnet-4-6
- via anthropic · 28% pass rate · 3.9s p95
Base pass rate
33%
Refined pass rate
28%
Refined p95
3.9s
Est. tokens saved
—
−0pts
no lift — the base model held its ground
0%
Base model0%
Invoked-refined▲3 improved▼0 regressed●5 unchanged
Per-row results
1Replacement cost vs ACV on a depreciated roof0% → 100%+100
2Coinsurance 80% clause recovery on an under-insured building0% → 0%0
3Aggregate deductible across a loss sequence under a per-occurrence + annual cap0% → 0%0
4Subrogation waiver interaction with additional-insured status0% → 100%+100
5Business-interruption period-of-restoration calculation100% → 100%0
6Pro-rata distribution across layered carriers on a covered loss0% → 0%0
7Suit-limitation clause: is a late-filed claim contractually barred?0% → 100%+100
8Named-peril coverage determination under a basic HO form0% → 0%0
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