Prove the lift · AI model performance evaluation
claude-opus-4-6 vs mixtral-8x7b
-10-point lift for claude-opus-4-6 on ecommerce-catalog-norm
Test summary
This benchmark evaluates claude-opus-4-6 against mixtral-8x7b on the ecommerce-catalog-norm v2 dataset (5 rows), scored by an LLM-as-judge (claude-haiku-4-5, run locally). claude-opus-4-6 reached a 15% pass rate versus 25% for mixtral-8x7b — a -10-point lift.
- Base model
- mixtral-8x7b
- via mistral · 25% pass rate
- Refined model
- claude-opus-4-6
- via anthropic · 15% pass rate · 0.6s p95
Base pass rate
25%
Refined pass rate
15%
Refined p95
0.6s
Est. tokens saved
857
−0pts
no lift — the base model held its ground
0%
Base model0%
Invoked-refined▲1 improved▼0 regressed●3 unchanged
Per-row results
1Normalize a free-text size into a standard enum100% → 100%0
2Deduplicate two near-identical SKUs0% → 0%0
3Classify a listing into the right category node100% → 100%0
4Extract material + color from a product title0% → 100%+100
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