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SSD MobileNet Mobilenet V1 Ssd on Google Coral Edge TPU: 1 row.

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

mobilenetssdmobilenet-v1-ssd on Google Coral Edge TPU: 1 row (1 measured, 0 derived). Expected: INT8 90.9 fps.

Change hardware, precision, runtime or add a comparison set on the live engine.

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
INT8fps190.990.990.9C1

Rows

PrecisionRuntimeInputPower modeSoftwareMetricClassDateSourceDerivationDupes
INT8edge tpu (inferred)224x224 b1m290.9 fpsC2023-Q1Google Coral · coral:docs/edgetpu/benchmarks · verified 2026-09-070

Cross-hardware comparison

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

HardwareBest valueClass
Google Coral Edge TPU90.9 fps
C

Assumptions

  • Rows from the research corpus do not state a runtime; the platform's native runtime (TensorRT / Edge TPU / Hailo SDK / RKNN / CPU) is assumed and flagged runtime_inferred.
  • 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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