HWBench

Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 vs Rockchip RK3576 (NPU, single core of 2)

Showing the newest results per platform and source. 18 superseded older results are hidden.Showing all results, including 18 superseded by newer results from the same source.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

Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0Rockchip RK3576 (NPU, single core of 2)
Best semantic segmentation303 FPS D
Older data (2020)
38.40 FPS C
2026-10-13 (page last edited)
Power2.00 W specn/a
Perf / W152 FPS/W specn/a
Pricen/an/a
Workloads with data1 of 75 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.

PlatformResultModel · precision · stackGradePowerSource
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)
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)

Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0:

◌

No published object detection results for Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 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.

PlatformResultModel · precision · stackGradePowerSource
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)
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)

Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0:

◌

No published instance segmentation results for Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 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.

PlatformResultModel · precision · stackGradePowerSource
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)
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)

Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0:

◌

No published pose estimation results for Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 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.

PlatformResultModel · precision · stackGradePowerSource
Rockchip RK3576 (NPU, single core of 2)459 FPS
throughput · b=1
mobilenetv2-12
INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · mobile-class CNN
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)

Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0:

◌

No published image classification results for Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 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.
PlatformResultModel · precision · stackGradePowerSource
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
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)
Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0
MIXED: model-size class mid-size CNN vs mobile-class CNN
303 FPS
inference_time · b=1
Unet Mv2 (128x128)
INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN
D2.00 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 USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 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

◌

No published LLM generation results for Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 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, 4.70×).

Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0Rockchip RK3576 (NPU, single core of 2)
Best image classification476 FPS D
Older data (2019)
459 FPS C
2026-10-13 (page last edited)
Power2.00 W specn/a
Perf / W238 FPS/W specn/a
Pricen/an/a
Workloads with data3 of 75 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).
PlatformResultModel · precision · stackGradePowerSource
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)
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)
Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0
MIXED: model-size class mobile-class CNN vs small (YOLO-s)
154 FPS
inference_time · b=1
MobileNet v1 SSD (224x224)
INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mobile-class CNN
D2.00 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 RK3576 (NPU, single core of 2) has published instance segmentation results.

PlatformResultModel · precision · stackGradePowerSource
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)
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)

Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0:

◌

No published instance segmentation results for Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 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.

PlatformResultModel · precision · stackGradePowerSource
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)
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)

Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0:

◌

No published pose estimation results for Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 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

✓ Like-for-like: model-size class mobile-class CNN, batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
Rockchip RK3576 (NPU, single core of 2)459 FPS
throughput · b=1
mobilenetv2-12
INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · mobile-class CNN
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)
Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0417 FPS
inference_time · b=1
MobileNet v1 (224x224)
INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mobile-class CNN
D2.00 W spec
platform spec envelope (not measured with this result)
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.
PlatformResultModel · precision · stackGradePowerSource
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
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)
Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.020.41 FPS
inference_time · b=1
ResNet-50 V1 (299x299)
INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN
D2.00 W spec
platform spec envelope (not measured with this result)
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.
PlatformResultModel · precision · stackGradePowerSource
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
Cunknown power n/a
no power published
Rockchip rknn_model_zoo README benchmark table
2026-10-13 (page last edited)
Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0
MIXED: model-size class mid-size CNN vs mobile-class CNN
303 FPS
inference_time · b=1
Unet Mv2 (128x128)
INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN
D2.00 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 USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 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

◌

No published LLM generation results for Google Coral USB Accelerator (Edge TPU) on Xeon Gold 6154 host, USB 3.0 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.

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.