Prove the lift · AI model performance evaluation
gemini-1.5-flash vs mixtral-8x7b
+11-point lift for gemini-1.5-flash on medical-coding-extract
Test summary
This benchmark evaluates gemini-1.5-flash against mixtral-8x7b on the medical-coding-extract v2 dataset (5 rows), scored by an LLM-as-judge (claude-haiku-4-5, run locally). gemini-1.5-flash reached a 55% pass rate versus 44% for mixtral-8x7b — a +11-point lift.
- Base model
- mixtral-8x7b
- via mistral · 44% pass rate
- Refined model
- gemini-1.5-flash
- via google · 55% pass rate · 1.9s p95
Base pass rate
44%
Refined pass rate
55%
Refined p95
1.9s
Est. tokens saved
9.5K
+0pts
refined beats base on 5 rows
0%
Base model0%
Invoked-refined▲3 improved▼0 regressed●2 unchanged
Per-row results
1Pull the procedure code from an operative report0% → 0%0
2Map a discharge summary to the primary ICD-10 code0% → 100%+100
3Identify a contraindication from a problem list0% → 100%+100
4Extract medication + dosage from a clinical note0% → 0%0
5Determine the correct E/M level from a visit note0% → 100%+100
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