Google Coral Dev Board (Edge TPU) vs Rockchip RK3566/RK3568 (NPU)
No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.
| Google Coral Dev Board (Edge TPU) | Rockchip RK3566/RK3568 (NPU) | |
|---|---|---|
| Best semantic segmentation | 175 FPS D Older data (2020) | 11.70 FPS C 2026-10-13 (page last edited) |
| Power | 2.00 W spec | n/a |
| Perf / W | 87.72 FPS/W spec | 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 RK3566/RK3568 (NPU) has published object detection results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Rockchip RK3566/RK3568 (NPU) | 27.10 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) |
Google Coral Dev Board (Edge TPU):
No published object detection results for Google Coral Dev Board (Edge TPU) or Rockchip RK3566/RK3568 (NPU) 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 RK3566/RK3568 (NPU) has published instance segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Rockchip RK3566/RK3568 (NPU) | 34.40 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) |
Google Coral Dev Board (Edge TPU):
No published instance segmentation results for Google Coral Dev Board (Edge TPU) or Rockchip RK3566/RK3568 (NPU) 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 RK3566/RK3568 (NPU) has published pose estimation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Rockchip RK3566/RK3568 (NPU) | 23.70 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) |
Google Coral Dev Board (Edge TPU):
No published pose estimation results for Google Coral Dev Board (Edge TPU) or Rockchip RK3566/RK3568 (NPU) 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 RK3566/RK3568 (NPU) has published image classification results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Rockchip RK3566/RK3568 (NPU) | 192 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) |
Google Coral Dev Board (Edge TPU):
No published image classification results for Google Coral Dev Board (Edge TPU) or Rockchip RK3566/RK3568 (NPU) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
semantic segmentation
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Rockchip RK3566/RK3568 (NPU) | 11.70 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) |
| Google Coral Dev Board (Edge TPU) MIXED: model-size class mid-size CNN vs mobile-class CNN | 175 FPS inference_time · b=1 | Unet Mv2 (128x128) INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN | D | 2.00 W spec platform spec envelope (not measured with this result) | Google Coral Edge TPU benchmarks page (Table 1) Older data (2020) |
No shared like-for-like group exists for this pair.
speech-to-text
No published speech-to-text results for Google Coral Dev Board (Edge TPU) or Rockchip RK3566/RK3568 (NPU) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
LLM generation
No published LLM generation results for Google Coral Dev Board (Edge TPU) or Rockchip RK3566/RK3568 (NPU) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
Split result: Google Coral Dev Board (Edge TPU) is faster in 1 and Rockchip RK3566/RK3568 (NPU) in 1 of 2 like-for-like comparisons.
| Google Coral Dev Board (Edge TPU) | Rockchip RK3566/RK3568 (NPU) | |
|---|---|---|
| Best image classification | 500 FPS D Older data (2019) | 192 FPS C 2026-10-13 (page last edited) |
| Power | 2.00 W spec | n/a |
| Perf / W | 250 FPS/W spec | 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
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Rockchip RK3566/RK3568 (NPU) | 27.10 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) |
| Google Coral Dev Board (Edge TPU) MIXED: model-size class mobile-class CNN vs small (YOLO-s) | 90.91 FPS inference_time · b=1 | MobileNet v1 SSD (224x224) INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mobile-class CNN | D | 2.00 W spec platform spec envelope (not measured with this result) | 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 RK3566/RK3568 (NPU) has published instance segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Rockchip RK3566/RK3568 (NPU) | 34.40 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) |
Google Coral Dev Board (Edge TPU):
No published instance segmentation results for Google Coral Dev Board (Edge TPU) or Rockchip RK3566/RK3568 (NPU) 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 RK3566/RK3568 (NPU) has published pose estimation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Rockchip RK3566/RK3568 (NPU) | 23.70 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) |
Google Coral Dev Board (Edge TPU):
No published pose estimation results for Google Coral Dev Board (Edge TPU) or Rockchip RK3566/RK3568 (NPU) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
image classification
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Google Coral Dev Board (Edge TPU) | 417 FPS inference_time · b=1 | MobileNet v1 (224x224) INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mobile-class CNN | D | 2.00 W spec platform spec envelope (not measured with this result) | Google Coral Edge TPU benchmarks page (Table 1) Older data (2019) |
| Rockchip RK3566/RK3568 (NPU) | 192 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) |
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Rockchip RK3566/RK3568 (NPU) | 38.60 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) |
| Google Coral Dev Board (Edge TPU) | 17.86 FPS inference_time · b=1 | ResNet-50 V1 (299x299) INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN | D | 2.00 W spec platform spec envelope (not measured with this result) | Google Coral Edge TPU benchmarks page (Table 1) Older data (2019) |
semantic segmentation
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Rockchip RK3566/RK3568 (NPU) | 11.70 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) |
| Google Coral Dev Board (Edge TPU) MIXED: model-size class mid-size CNN vs mobile-class CNN | 175 FPS inference_time · b=1 | Unet Mv2 (128x128) INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN | D | 2.00 W spec platform spec envelope (not measured with this result) | Google Coral Edge TPU benchmarks page (Table 1) Older data (2020) |
No shared like-for-like group exists for this pair.
speech-to-text
No published speech-to-text results for Google Coral Dev Board (Edge TPU) or Rockchip RK3566/RK3568 (NPU) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
LLM generation
No published LLM generation results for Google Coral Dev Board (Edge TPU) or Rockchip RK3566/RK3568 (NPU) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
How to read these numbers
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.