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Benchmark Explorer · MobileNetV2v2 on Jetson Orin Nano Super

MobileNetV2v2 on Jetson Orin Nano Super: 2 rows.

Method v1.4.1 · dataset 2026-09-29 · verified 2026-09-16 · last updated September 2026

mobilenetv2v2 on Jetson Orin Nano Super: 2 rows (2 measured, 0 derived). Measured share for this scope: 70% of 63 rows (class C). Expected: FP16 1176.5 fps; INT8 1280.4 fps. Fastest: Jetson Thor T5000 4004 fps (class D), Hailo-10H 2944 fps (class D), Hailo-8 2597 fps (class C).

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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
FP16fps11176.51176.51176.5C1
INT8fps11280.41280.41280.4C1

Rows

PrecisionRuntimeInputPower modeSoftwareMetricClassDateSourceDerivationDupes
INT8tensorrt224x224 b1maxn_superjetpack L4T R36.4.7, TensorRT 10.3.01280.4 fpsC2026onnxsim · bench:onnxsim-readme-modelopt-int8-and-tensorrt-latency-jetson-orin-nano-8gb-on-jetpack-6 L4T R36.4.7, TensorRT 10.3.0 · verified 2026-09-280
FP16tensorrt224x224 b1maxn_superjetpack L4T R36.4.7, TensorRT 10.3.01176.5 fpsC2026onnxsim · bench:onnxsim-readme-modelopt-int8-and-tensorrt-latency-jetson-orin-nano-8gb-on-jetpack-6 L4T R36.4.7, TensorRT 10.3.0 · verified 2026-09-280

Cross-hardware comparison

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

HardwareBest valueClass
Jetson Thor T50004004 fps
D
Hailo-10H2944 fps
D
Hailo-82597 fps
C
Hailo-8L1738 fps
C
Jetson Orin Nano Super1280.4 fps
C
Jetson Orin NX 16GB1250 fps
D
Rockchip RK3588 NPU450.7 fps
C
Rockchip RK3588S450.7 fps
D
Rockchip RK3568180.7 fps
C

Assumptions

  • Latency provenance: 0 of the 2 matching rows that report a latency computed it as 1000/fps rather than measuring it (latency_source → derived_reciprocal); 2 were observed independently. Every p99 in the database is a modelled 1.20–1.43× tail over the p50, never an observed one.
  • 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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