Prove the lift · AI model performance evaluation
mistral-large vs llama-3.1-70b
+1-point lift for mistral-large on support-ticket-triage
Test summary
This benchmark evaluates mistral-large against llama-3.1-70b on the support-ticket-triage v2 dataset (6 rows), scored by an LLM-as-judge (claude-haiku-4-5, run locally). mistral-large reached a 31% pass rate versus 30% for llama-3.1-70b — a +1-point lift.
- Base model
- llama-3.1-70b
- via ollama · 30% pass rate
- Refined model
- mistral-large
- via mistral · 31% pass rate · 2.6s p95
Base pass rate
30%
Refined pass rate
31%
Refined p95
2.6s
Est. tokens saved
4.8K
+0pts
refined beats base on 6 rows
0%
Base model0%
Invoked-refined▲3 improved▼1 regressed●2 unchanged
Per-row results
1Extract the affected order id from a free-text complaint0% → 100%+100
2Detect churn-risk sentiment in a renewal thread100% → 100%0
3Summarize a 12-message thread into a one-line disposition0% → 0%0
4Priority-tag an outage report vs a feature question0% → 100%+100
5Route a multi-part ticket to the correct queue0% → 100%+100
6Classify: billing dispute vs refund request vs cancellation100% → 0%-100
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