Prove the lift · AI model performance evaluation
llama-3.1-70b vs mistral-large
+14-point lift for llama-3.1-70b on ecommerce-catalog-norm
Test summary
This benchmark evaluates llama-3.1-70b against mistral-large on the ecommerce-catalog-norm v1 dataset (5 rows), scored by an LLM-as-judge (gpt-4o-mini, run locally). llama-3.1-70b reached a 53% pass rate versus 39% for mistral-large — a +14-point lift.
- Base model
- mistral-large
- via mistral · 39% pass rate
- Refined model
- llama-3.1-70b
- via ollama · 53% pass rate · 3.6s p95
Base pass rate
39%
Refined pass rate
53%
Refined p95
3.6s
Est. tokens saved
7.4K
+0pts
refined beats base on 5 rows
0%
Base model0%
Invoked-refined▲1 improved▼0 regressed●3 unchanged
Per-row results
1Deduplicate two near-identical SKUs100% → 100%0
2Extract material + color from a product title100% → 100%0
3Classify a listing into the right category node0% → 100%+100
4Normalize a free-text size into a standard enum100% → 100%0
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