Prove the lift · AI model performance evaluation

llama-3.1-405b vs grok-4

-4-point lift for llama-3.1-405b on ecommerce-catalog-norm

Test summary

This benchmark evaluates llama-3.1-405b against grok-4 on the ecommerce-catalog-norm v3 dataset (5 rows), scored by an LLM-as-judge (llama-3.1-8b). llama-3.1-405b reached a 61% pass rate versus 65% for grok-4 — a -4-point lift.

Base model
grok-4
via xai · 65% pass rate
Refined model
llama-3.1-405b
via meta · 61% pass rate · 3.0s p95
Base pass rate
65%
Refined pass rate
61%
Refined p95
3.0s
Est. tokens saved
239
−0pts
no lift — the base model held its ground
0%
Base model
0%
Invoked-refined
▲2 improved▼0 regressed●2 unchanged

Per-row results

1Extract material + color from a product title100% → 100%0
2Classify a listing into the right category node0% → 100%+100
3Deduplicate two near-identical SKUs0% → 100%+100
4Normalize a free-text size into a standard enum100% → 100%0
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