Repo · Benchmarks & research
jevbench (dhruvmehra)
Reproduce TypeSafe Jev vs LLM/BERT/Laya/NLI text-classification accuracy, calibration, latency, throughput, and cost on public datasets
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Benchmark TypeSafe JEV against LLMs, fine-tuned BERT, Laya and zero-shot NLI on text classification: accuracy, calibration, latency, throughput, cost
How builders describe it
Benchmark TypeSafe JEV against LLMs, fine-tuned BERT, Laya and zero-shot NLI on text classification: accuracy, calibration, latency, throughput, cost.
The decision Jev makes
Benchmark questions with known answers, to check accuracy and confidence.
Where it fits
Head-to-head tests, calibration studies and independent research into how well Jev decides, how fast, and at what cost. All 682 benchmarks & research projects →
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