NVIDIA Jetson AGX Orin 64GB vs Rockchip RK1808 (NPU)

NVIDIA Jetson AGX Orin developer kit with its retail box, on a black background — NVIDIA Jetson AGX Orin developer kit. Photo: Auledas, CC BY 4.0, via Wikimedia Commons.

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Showing the newest results per platform and source. 12 superseded older results are hidden.Showing all results, including 12 superseded by newer results from the same source.

NVIDIA Jetson AGX Orin 64GB is faster in all 3 like-for-like comparisons (largest gap: object detection, 6.51×).

	NVIDIA Jetson AGX Orin 64GB	Rockchip RK1808 (NPU)
Best object detection	435 FPS B 2026-10-13 (page last edited)	66.80 FPS C 2026-10-13 (page last edited)
Power	65.00 W spec	n/a
Perf / W	6.69 FPS/W spec	n/a
Price	$3499 list	n/a
Workloads with data	3 of 7	4 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 nano (YOLO-n), batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	435 FPS inference_time · b=1	YOLO26n INT8 · Ultralytics TensorRT · nano (YOLO-n)	B	65.00 W spec platform spec envelope (not measured with this result)	Ultralytics documentation (benchmark table) 2026-10-13 (page last edited)
Rockchip RK1808 (NPU)	66.80 FPS throughput · b=1	yolov6n 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)

✓ Like-for-like: model-size class small (YOLO-s), batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	80.90 FPS throughput · b=1	YOLO11s (640x640) INT8 · TensorRT (ONNX export) · small (YOLO-s)	C	65.00 W spec platform spec envelope (not measured with this result)	arXiv 2608.00927 AgriJetsonBench (abstract figures) 2026-08-02 (published)
Rockchip RK1808 (NPU)	37.20 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)

instance segmentation

Only Rockchip RK1808 (NPU) has published instance segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK1808 (NPU)	49.60 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)

NVIDIA Jetson AGX Orin 64GB:

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No published instance segmentation results for NVIDIA Jetson AGX Orin 64GB or Rockchip RK1808 (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

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No published pose estimation results for NVIDIA Jetson AGX Orin 64GB or Rockchip RK1808 (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 RK1808 (NPU) has published image classification results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK1808 (NPU)	170 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)

NVIDIA Jetson AGX Orin 64GB:

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No published image classification results for NVIDIA Jetson AGX Orin 64GB or Rockchip RK1808 (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

✓ 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
NVIDIA Jetson AGX Orin 64GB	104 FPS throughput · b=1	SegFormer-B0 (640x640) FP16 · TensorRT (ONNX export) · unknown	C	65.00 W spec platform spec envelope (not measured with this result)	arXiv 2608.00927 AgriJetsonBench (abstract figures) 2026-08-02 (published)
Rockchip RK1808 (NPU)	20.90 FPS throughput · b=1	ppseg_lite_1024x512 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)

speech-to-text

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No published speech-to-text results for NVIDIA Jetson AGX Orin 64GB or Rockchip RK1808 (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

Only NVIDIA Jetson AGX Orin 64GB has published LLM generation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	30.00 tok/s generation_throughput · b=1	Qwen 3 8B W4A16 · vLLM · LLM 5–14B	C	65.00 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson AI Lab benchmarks (benchmarks.json) 2026-07-21 (page last edited)

Rockchip RK1808 (NPU):

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No published LLM generation results for Rockchip RK1808 (NPU) or NVIDIA Jetson AGX Orin 64GB yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

NVIDIA Jetson AGX Orin 64GB is faster in all 3 like-for-like comparisons (largest gap: object detection, 6.51×).

	NVIDIA Jetson AGX Orin 64GB	Rockchip RK1808 (NPU)
Best object detection	435 FPS B 2026-10-13 (page last edited)	66.80 FPS C 2026-10-13 (page last edited)
Power	65.00 W spec	n/a
Perf / W	6.69 FPS/W spec	n/a
Price	$3499 list	n/a
Workloads with data	5 of 7	4 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 nano (YOLO-n), batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	435 FPS inference_time · b=1	YOLO26n INT8 · Ultralytics TensorRT · nano (YOLO-n)	B	65.00 W spec platform spec envelope (not measured with this result)	Ultralytics documentation (benchmark table) 2026-10-13 (page last edited)
Rockchip RK1808 (NPU)	66.80 FPS throughput · b=1	yolov6n 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)

✓ Like-for-like: model-size class small (YOLO-s), batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	80.90 FPS throughput · b=1	YOLO11s (640x640) INT8 · TensorRT (ONNX export) · small (YOLO-s)	C	65.00 W spec platform spec envelope (not measured with this result)	arXiv 2608.00927 AgriJetsonBench (abstract figures) 2026-08-02 (published)
Rockchip RK1808 (NPU)	37.20 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)

instance segmentation

Only Rockchip RK1808 (NPU) has published instance segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK1808 (NPU)	49.60 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)

NVIDIA Jetson AGX Orin 64GB:

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pose estimation

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image classification

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

Platform	Result	Model · precision · stack	Grade	Power	Source
Rockchip RK1808 (NPU)	170 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)
NVIDIA Jetson AGX Orin 64GB MIXED: model-size class mid-size CNN vs mobile-class CNN; batch unknown vs 1	6424 FPS throughput_offline · b=unknown	MLPerf ResNet INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · mid-size CNN	D	65.00 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson Benchmarks (MLPerf v3.1 results table) Older data (2023)

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

semantic segmentation

✓ 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
NVIDIA Jetson AGX Orin 64GB	104 FPS throughput · b=1	SegFormer-B0 (640x640) FP16 · TensorRT (ONNX export) · unknown	C	65.00 W spec platform spec envelope (not measured with this result)	arXiv 2608.00927 AgriJetsonBench (abstract figures) 2026-08-02 (published)
Rockchip RK1808 (NPU)	20.90 FPS throughput · b=1	ppseg_lite_1024x512 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)

speech-to-text

Only NVIDIA Jetson AGX Orin 64GB has published speech-to-text results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	1170 FPS throughput_offline · b=unknown	MLPerf RNN-T INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · RNN-T	D	65.00 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson Benchmarks (MLPerf v3.1 results table) Older data (2023)

Rockchip RK1808 (NPU):

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No published speech-to-text results for Rockchip RK1808 (NPU) or NVIDIA Jetson AGX Orin 64GB yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

LLM generation

Only NVIDIA Jetson AGX Orin 64GB has published LLM generation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	30.00 tok/s generation_throughput · b=1	Qwen 3 8B W4A16 · vLLM · LLM 5–14B	C	65.00 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson AI Lab benchmarks (benchmarks.json) 2026-07-21 (page last edited)

Rockchip RK1808 (NPU):

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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.