Repo · Benchmarks & research
edgejev
离线可用的本地类型化决策：4 核 CPU 单题 15.6ms。Local & offline Jev / System One inference on CPU — ONNX + INT8, no torch at runtime.
Open github.com ↗From the repository
离线可用的本地类型化决策：4 核 CPU 单题 15.6ms。Local & offline Jev / System One inference on CPU — ONNX + INT8, no torch at runtime. 支持 laya / kev / PlayJev
calibrated-probabilitiescpu-inferencedecision-modeledge-aiint8jevkevlayallm-inferencelocal-inferencemodel-quantizationoffline-firstoffline-inferenceon-device-aionnxonnxruntimequantizationsystem-onetyped-decisionstypesafe-ai
How builders describe it
离线可用的本地类型化决策：4 核 CPU 单题 15.6ms。Local & offline Jev / System One inference on CPU — ONNX + INT8, no torch at runtime. 支持 laya / kev / PlayJev.
Local offline pipeline that converts open Jev reproductions to ONNX, applies quantization, and serves typed decisions on CPU with a protocol-compatible endpoint.
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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