Prove the lift · AI model performance evaluation

claude-sonnet-4-6 vs mixtral-8x7b

-4-point lift for claude-sonnet-4-6 on medical-coding-extract

Test summary

This benchmark evaluates claude-sonnet-4-6 against mixtral-8x7b on the medical-coding-extract v3 dataset (5 rows), scored by an LLM-as-judge (llama-3.1-8b). claude-sonnet-4-6 reached a 47% pass rate versus 51% for mixtral-8x7b — a -4-point lift.

Base model
mixtral-8x7b
via mistral · 51% pass rate
Refined model
claude-sonnet-4-6
via anthropic · 47% pass rate · 0.9s p95
Base pass rate
51%
Refined pass rate
47%
Refined p95
0.9s
Est. tokens saved
1.3K
0pts
no lift — the base model held its ground
0%
Base model
0%
Invoked-refined
1 improved0 regressed4 unchanged

Per-row results

1Determine the correct E/M level from a visit note100%100%0
2Identify a contraindication from a problem list0%100%+100
3Map a discharge summary to the primary ICD-10 code100%100%0
4Extract medication + dosage from a clinical note100%100%0
5Pull the procedure code from an operative report100%100%0
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