Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) vs Rockchip RK3576 (NPU, single core of 2)

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Showing the newest results per platform and source. 18 superseded older results are hidden.Showing all results, including 18 superseded by newer results from the same source.

No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.

	Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only)	Rockchip RK3576 (NPU, single core of 2)
Best semantic segmentation	5.24 FPS D Older data (2020)	38.40 FPS C 2026-10-13 (page last edited)
Power	n/a	n/a
Perf / W	n/a	n/a
Price	n/a	n/a
Workloads with data	1 of 7	5 of 7

Best published semantic segmentation result per platform. n/a = not published; never estimated.

Show data — all workloads, sources and like-for-like groups

object detection

Only Rockchip RK3576 (NPU, single core of 2) has published object detection results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3576 (NPU, single core of 2)	65.10 FPS throughput · b=1	yolov5s_relu INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · small (YOLO-s)	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)

Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):

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No published object detection results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or Rockchip RK3576 (NPU, single core of 2) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

instance segmentation

Only Rockchip RK3576 (NPU, single core of 2) has published instance segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3576 (NPU, single core of 2)	96.40 FPS throughput · b=1	yolov5n-seg INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · nano (YOLO-n)	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)

Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):

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No published instance segmentation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or Rockchip RK3576 (NPU, single core of 2) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

pose estimation

Only Rockchip RK3576 (NPU, single core of 2) has published pose estimation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3576 (NPU, single core of 2)	75.00 FPS throughput · b=1	yolov8n-pose INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · nano (YOLO-n)	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)

Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):

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No published pose estimation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or Rockchip RK3576 (NPU, single core of 2) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

image classification

Only Rockchip RK3576 (NPU, single core of 2) has published image classification results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3576 (NPU, single core of 2)	459 FPS throughput · b=1	mobilenetv2-12 INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · mobile-class CNN	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)

Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):

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No published image classification results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or Rockchip RK3576 (NPU, single core of 2) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

semantic segmentation

⚠ MIXED COMPARISON — not like-for-like. Baseline mobile-class CNN at batch 1. Differs: model-size class mid-size CNN vs mobile-class CNN.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3576 (NPU, single core of 2)	37.80 FPS throughput · b=1	deeplab-v3-plus-mobilenet-v2 INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · mobile-class CNN	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) CPU-only MIXED: model-size class mid-size CNN vs mobile-class CNN	5.24 FPS inference_time · b=1	Unet Mv2 (128x128) TFLite on CPU · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN	D	unknown power n/a no power published	Google Coral Edge TPU benchmarks page (Table 1) Older data (2020)

No shared like-for-like group exists for this pair.

speech-to-text

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No published speech-to-text results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or Rockchip RK3576 (NPU, single core of 2) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

LLM generation

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No published LLM generation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or Rockchip RK3576 (NPU, single core of 2) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

Rockchip RK3576 (NPU, single core of 2) is faster in all 2 like-for-like comparisons (largest gap: image classification, 168×).

	Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only)	Rockchip RK3576 (NPU, single core of 2)
Best image classification	8.20 FPS D Older data (2019)	459 FPS C 2026-10-13 (page last edited)
Power	n/a	n/a
Perf / W	n/a	n/a
Price	n/a	n/a
Workloads with data	3 of 7	5 of 7

Best published image classification result per platform (may be from different like-for-like groups — see data). n/a = not published; never estimated.

Show data — all workloads, sources and like-for-like groups

object detection

⚠ MIXED COMPARISON — not like-for-like. Baseline small (YOLO-s) at batch 1. Differs: model-size class mobile-class CNN vs small (YOLO-s).

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3576 (NPU, single core of 2)	65.10 FPS throughput · b=1	yolov5s_relu INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · small (YOLO-s)	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) CPU-only MIXED: model-size class mobile-class CNN vs small (YOLO-s)	3.55 FPS inference_time · b=1	MobileNet v2 SSD (224x224) TFLite on CPU · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mobile-class CNN	D	unknown power n/a no power published	Google Coral Edge TPU benchmarks page (Table 1) Older data (2019)

No shared like-for-like group exists for this pair.

instance segmentation

Only Rockchip RK3576 (NPU, single core of 2) has published instance segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3576 (NPU, single core of 2)	96.40 FPS throughput · b=1	yolov5n-seg INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · nano (YOLO-n)	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)

Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):

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pose estimation

Only Rockchip RK3576 (NPU, single core of 2) has published pose estimation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3576 (NPU, single core of 2)	75.00 FPS throughput · b=1	yolov8n-pose INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · nano (YOLO-n)	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)

Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):

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image classification

✓ Like-for-like: model-size class mobile-class CNN, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3576 (NPU, single core of 2)	459 FPS throughput · b=1	mobilenetv2-12 INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · mobile-class CNN	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) CPU-only	8.20 FPS inference_time · b=1	MobileNet v2 (224x224) TFLite on CPU · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mobile-class CNN	D	unknown power n/a no power published	Google Coral Edge TPU benchmarks page (Table 1) Older data (2019)

✓ Like-for-like: model-size class mid-size CNN, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3576 (NPU, single core of 2)	96.00 FPS throughput · b=1	resnet50-v2-7 INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · mid-size CNN	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) CPU-only	0.570 FPS inference_time · b=1	ResNet-50 V1 (299x299) TFLite on CPU · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN	D	unknown power n/a no power published	Google Coral Edge TPU benchmarks page (Table 1) Older data (2019)

semantic segmentation

⚠ MIXED COMPARISON — not like-for-like. Baseline mobile-class CNN at batch 1. Differs: model-size class mid-size CNN vs mobile-class CNN.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3576 (NPU, single core of 2)	37.80 FPS throughput · b=1	deeplab-v3-plus-mobilenet-v2 INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · mobile-class CNN	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) CPU-only MIXED: model-size class mid-size CNN vs mobile-class CNN	5.24 FPS inference_time · b=1	Unet Mv2 (128x128) TFLite on CPU · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN	D	unknown power n/a no power published	Google Coral Edge TPU benchmarks page (Table 1) Older data (2020)

No shared like-for-like group exists for this pair.

speech-to-text

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LLM generation

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How to read these numbers

Every number is labelled. Confidence: A MLPerf closed, audited · B documented third-party method · C community / review · D vendor-published, not independently verified · E estimate. Power basis: measured with the result · spec vendor spec/envelope · power n/a not published.

Machine-readable: /find.json (see llms.txt); full tables are in “Show data”. Confidence grades: A audited MLPerf closed · B documented third-party · C community · D vendor-published · E estimate. Unknown values are shown as unknown, never estimated. Generated 2026-10-16 from public sources.