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YOLO12n on Jetson Thor T5000: 1 row.

Method v1.0 · dataset 2026-09-07 · verified 2026-09-07 · last updated September 2026

yolo12n on Jetson Thor T5000: 1 row (1 measured, 0 derived). Expected: FP16 719 fps. Fastest: Jetson Thor T5000 719 fps (class C), Jetson AGX Orin 64GB 416.5 fps (class D), Jetson Orin Nano Super 228.1 fps (class D).

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Expected range per precision

Min / median / max of the matching rows, all classes. When a precision has no row, the estimator's benchmark hierarchy (B → C → D) supplies a fallback with its tier chain reported.

PrecisionMetricNMinMedianMaxBest classMeasured
FP16fps1719719719C1

Rows

PrecisionRuntimeInputPower modeSoftwareMetricClassDateSourceDerivationDupes
FP16tensorrt640x640 b1130wultralytics 8.4.7719 fpsC2025Ultralytics · bench:ultralytics-yolo12-jetson 8.4.7 · verified 2026-09-070

Cross-hardware comparison

Best row per hardware for the same model and precision, relative to the fastest.

HardwareBest valueClass
Jetson Thor T5000719 fps
C
Jetson AGX Orin 64GB416.5 fps
D
Jetson Orin Nano Super228.1 fps
D
Jetson Orin NX 16GB218 fps
D

Assumptions

  • Class C = measured and published by the source named on the row; class D = EdgeAIStack-derived (derivation stated). Rows are inference-only unless scope says end_to_end; publisher measurement conditions (JetPack, batch, warm-up) are in the linked page.

Method and limitations

Rows are read from the normalised benchmark database (publisher benchmarks and research-derived rows, deduplicated per hardware × model × runtime × precision × input × power mode, best evidence kept). Expected range = min / median / max of the matching rows per precision; when a precision has no row the estimator's benchmark hierarchy (B → C → D) is consulted and its tier chain reported. Comparison = best row per hardware for the same model and precision, relative to the fastest. Nothing is scored; every number carries its class and source line.

Full method, dedupe rule, evidence classes and the confidence rule: Benchmark Explorer methodology.

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