Repo · Benchmarks & research
TetraJev
Jev-class decisions on bounded decision problems from two frozen open-weight readers — four readings per item, fit-free fusion, agreement routing,…
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High-performance, high-precision, locally-fast-deployed Jev-class decision service — four readings, one routed decision, zero training.
decision-routingjevllmlocal-inferenceopen-weightszero-training
How builders describe it
High-performance, high-precision, locally-fast-deployed Jev-class decision service — four readings, one routed decision, zero training.
Jev-class decisions on bounded decision problems from two frozen open-weight readers — four readings per item, fit-free fusion, agreement routing, and published coverage–accuracy curves; no fine-tuning and no distillation.
Two frozen open-weight Qwen3.5 models read each task four ways, a letter and a pair readout each, and a fit-free fusion plus an agreement router turn those readings into calibrated decisions, with no fine-tuning and no distillation anywhere in the pipeline.
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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