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DeepSeek Chat

Appears in 6 benchmarksMean lean (confidence − pass rate): +0.054/6 benchmarks lean overconfident (prospective probe)

Positioning spread

0.000.250.500.751.00SQuAD (factual recall)MMLU-Pro (knowledge)LegalBench (legal reasoning)MathBench (competition math)OmniMath (advanced math)SciCode (scientific code)performanceconfidence (red gap = overconfident)
Performance vs. confidence for DeepSeek Chat, per benchmark (prospective probe).
BenchmarkTask accConfidenceF₁Leans
SQuAD (factual recall)0.550.320.57-0.23 cautious
MMLU-Pro (knowledge)0.510.890.69+0.38 overconfident
LegalBench (legal reasoning)0.840.570.67-0.27 cautious
MathBench (competition math)0.950.970.96+0.03 calibrated
OmniMath (advanced math)0.560.840.71+0.28 overconfident
SciCode (scientific code)0.550.680.68+0.13 overconfident

In the full cloud

-3-3-2-2-1-100112233Performance z-score within benchmark/probe →Confidence z-score →
DeepSeek Chat conditions all other model/condition points equal relative confidence and pass rate

Pairwise footprint

Match accuracy controls for the performance base-rate gap
DeepSeek Chat pairs
18/ 171
DeepSeek Chat mean tau
+0.017
All-pairs mean
+0.037
DeepSeek Chat p<0.05
6(33.3%)
-1.0-0.50.00.51.0Pair signal: do confidence gaps rank performance gaps? (Kendall tau-b)
all model pairs (observed) base-rate-matched null calibration-preserving null DeepSeek Chat pair (filled = p<0.05) DeepSeek Chat mean all-pairs mean
vs DeepSeek R1 → Compare with anything →