Rockchip RK3588 (NPU, single core of 3) vs Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)

Close-up of a Rockchip RK3588 system-on-chip package on a circuit board — Rockchip RK3588 SoC package. Photo: Popolon (Commons uploader; CC0, attribution not required), CC0, via Wikimedia Commons.

AlteraFPGA (PCIe/dev kit)No licensed photo yet

Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) is faster in all 3 like-for-like comparisons (largest gap: image classification, 3.03×).

	Rockchip RK3588 (NPU, single core of 3)	Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
Best object detection	109 FPS C 2026-10-13 (page last edited)	117 FPS D 2026-08-10 (published)
Power	n/a	n/a
Perf / W	n/a	n/a
Price	n/a	n/a
Workloads with data	5 of 7	3 of 7

Best published object detection 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

✓ Like-for-like: model-size class unknown, batch 1 (size or batch not stated by source — unverified). Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)	117 FPS throughput · b=1	yolo-v3-tiny-tf FP16 · FPGA AI Suite 2026.1.1 / OpenVINO; IP throughput (hostless) · unknown	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)
Rockchip RK3588 (NPU, single core of 3)	73.60 FPS throughput · b=1	yolov7-tiny INT8 · RKNN-Toolkit2 / RKNPU (rknn_model_zoo) · unknown	C	unknown power n/a no power published	Rockchip rknn_model_zoo README benchmark table 2026-10-13 (page last edited)

instance segmentation

Only Rockchip RK3588 (NPU, single core of 3) has published instance segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3588 (NPU, single core of 3)	71.50 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)

Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite):

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No published instance segmentation results for Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) or Rockchip RK3588 (NPU, single core of 3) 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 RK3588 (NPU, single core of 3) has published pose estimation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK3588 (NPU, single core of 3)	58.30 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)

Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite):

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No published pose estimation results for Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) or Rockchip RK3588 (NPU, single core of 3) 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.

Platform	Result	Model · precision · stack	Grade	Power	Source
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)	1391 FPS throughput · b=1	mobilenet-v1-1.0-224 not stated in table (set by .arch file) · FPGA AI Suite 2026.1.1 / OpenVINO; IP throughput (hostless) · mobile-class CNN	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)
Rockchip RK3588 (NPU, single core of 3)	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)

✓ 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
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)	220 FPS throughput · b=1	resnet-50-tf not stated in table (set by .arch file) · FPGA AI Suite 2026.1.1 / OpenVINO; IP throughput (hostless) · mid-size CNN	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)
Rockchip RK3588 (NPU, single core of 3)	113 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)

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 RK3588 (NPU, single core of 3)	34.70 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)
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) MIXED: model-size class mid-size CNN vs mobile-class CNN	10.26 FPS throughput · b=1	unet-camvid-onnx-0001 not stated in table (set by .arch file) · FPGA AI Suite 2026.1.1 / OpenVINO; IP throughput (hostless) · mid-size CNN	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)

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

speech-to-text

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No published speech-to-text results for Rockchip RK3588 (NPU, single core of 3) or Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) 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 Rockchip RK3588 (NPU, single core of 3) or Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) 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.