Prove the lift · AI model performance evaluation
gemini-1.5-pro vs mistral-large
+18-point lift for gemini-1.5-pro on ecommerce-catalog-norm
Test summary
This benchmark evaluates gemini-1.5-pro against mistral-large on the ecommerce-catalog-norm v1 dataset (5 rows), scored by an LLM-as-judge (llama-3.1-8b). gemini-1.5-pro reached a 68% pass rate versus 50% for mistral-large — a +18-point lift.
- Base model
- mistral-large
- via mistral · 50% pass rate
- Refined model
- gemini-1.5-pro
- via google · 68% pass rate · 3.6s p95
Base pass rate
50%
Refined pass rate
68%
Refined p95
3.6s
Est. tokens saved
8.1K
+0pts
refined beats base on 5 rows
0%
Base model0%
Invoked-refined▲1 improved▼2 regressed●1 unchanged
Per-row results
1Classify a listing into the right category node100% → 100%0
2Extract material + color from a product title0% → 100%+100
3Deduplicate two near-identical SKUs100% → 0%-100
4Normalize a free-text size into a standard enum100% → 0%-100
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