NVIDIA Jetson AGX Orin 64GB vs Rockchip RK3566/RK3568 (NPU)

NVIDIA Jetson AGX Orin 64GB is faster in all 3 like-for-like comparisons (largest gap: semantic segmentation, 15.70×).
| NVIDIA Jetson AGX Orin 64GB | Rockchip RK3566/RK3568 (NPU) | |
|---|---|---|
| Best object detection | 435 FPS B 2026-10-13 (page last edited) | 49.90 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 | 5 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
| 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 RK3566/RK3568 (NPU) | 49.90 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) |
| 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 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) |
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) |
NVIDIA Jetson AGX Orin 64GB:
No published instance segmentation results for NVIDIA Jetson AGX Orin 64GB 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) |
NVIDIA Jetson AGX Orin 64GB:
No published pose estimation results for NVIDIA Jetson AGX Orin 64GB 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) |
NVIDIA Jetson AGX Orin 64GB:
No published image classification results for NVIDIA Jetson AGX Orin 64GB 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 |
|---|---|---|---|---|---|
| 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 RK3566/RK3568 (NPU) | 6.60 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
No published speech-to-text results for NVIDIA Jetson AGX Orin 64GB 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
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 RK3566/RK3568 (NPU):
No published LLM generation results for Rockchip RK3566/RK3568 (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: semantic segmentation, 15.70×).
| NVIDIA Jetson AGX Orin 64GB | Rockchip RK3566/RK3568 (NPU) | |
|---|---|---|
| Best object detection | 435 FPS B 2026-10-13 (page last edited) | 49.90 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 | 5 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
| 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 RK3566/RK3568 (NPU) | 49.90 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) |
| 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 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) |
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) |
NVIDIA Jetson AGX Orin 64GB:
No published instance segmentation results for NVIDIA Jetson AGX Orin 64GB 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) |
NVIDIA Jetson AGX Orin 64GB:
No published pose estimation results for NVIDIA Jetson AGX Orin 64GB 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 |
|---|---|---|---|---|---|
| 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) |
| 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
| 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 RK3566/RK3568 (NPU) | 6.60 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 RK3566/RK3568 (NPU):
No published speech-to-text results for Rockchip RK3566/RK3568 (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 RK3566/RK3568 (NPU):
No published LLM generation results for Rockchip RK3566/RK3568 (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.
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.