HWBench

AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) vs NVIDIA Jetson Orin Nano Super

FPGA / Versal coverage note: 1,243 rows come from the AMD Vitis AI 3.0/3.5 Model Zoo tables; 733 (59%) are image classification. Detection, segmentation and other workloads are thinner, and there is no LLM or speech data for these boards. All are vendor-published (grade D). FPGA / Versal overview.

No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.

AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)NVIDIA Jetson Orin Nano Super
Best object detection6100 FPS D
Older data (2023)
263 FPS B
2026-10-13 (page last edited)
Power75.00 W spec25.00 W spec
Perf / W81.34 FPS/W spec10.53 FPS/W spec
Pricen/a$249 list
Workloads with data4 of 72 of 7

Best published object detection result per platform. 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 nano (YOLO-n) at batch 1. Differs: model-size class mobile-class CNN vs nano (YOLO-n); batch unknown vs 1.
PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson Orin Nano Super263 FPS
inference_time · b=1
YOLO26n
INT8 · Ultralytics TensorRT · nano (YOLO-n)
B25.00 W spec
reported in result source — spec
Ultralytics documentation (benchmark table)
2026-10-13 (page last edited)
AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)
MIXED: model-size class mobile-class CNN vs nano (YOLO-n); batch unknown vs 1
6100 FPS
E2E throughput, multi thread · b=unknown
tf_ssdmobilenetv1_3.5
INT8 · Vitis AI 3.5 (VART) · mobile-class CNN
D75.00 W spec
reported in result source — spec
Vitis AI 3.5 Model Zoo performance table
Older data (2023)

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

instance segmentation

◌

No published instance segmentation results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or NVIDIA Jetson Orin Nano Super 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 AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) has published pose estimation results.

PlatformResultModel · precision · stackGradePowerSource
AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)8327 FPS
E2E throughput, multi thread · b=unknown
pt_movenet_3.5
INT8 · Vitis AI 3.5 (VART) · mobile-class CNN
D75.00 W spec
reported in result source — spec
Vitis AI 3.5 Model Zoo performance table
Older data (2023)

NVIDIA Jetson Orin Nano Super:

◌

No published pose estimation results for NVIDIA Jetson Orin Nano Super or AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) 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 AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) has published image classification results.

PlatformResultModel · precision · stackGradePowerSource
AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)7780 FPS
E2E throughput, multi thread · b=unknown
pt_OFA-resnet50_0.88_3.5
INT8 · Vitis AI 3.5 (VART) · mid-size CNN
D75.00 W spec
reported in result source — spec
Vitis AI 3.5 Model Zoo performance table
Older data (2023)

NVIDIA Jetson Orin Nano Super:

◌

No published image classification results for NVIDIA Jetson Orin Nano Super or AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) 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 mid-size CNN at batch unknown. Differs: model-size class unknown vs mid-size CNN; batch 1 vs unknown.
PlatformResultModel · precision · stackGradePowerSource
AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)1177 FPS
E2E throughput, multi thread · b=unknown
tf2_2D-UNET_3.5
INT8 · Vitis AI 3.5 (VART) · mid-size CNN
D75.00 W spec
reported in result source — spec
Vitis AI 3.5 Model Zoo performance table
Older data (2023)
NVIDIA Jetson Orin Nano Super
MIXED: model-size class unknown vs mid-size CNN; batch 1 vs unknown
67.47 FPS
throughput · b=1
SegFormer-B0 (640x640)
FP16 · TensorRT (ONNX export) · unknown
C25.00 W spec
platform spec envelope (not measured with this result)
arXiv 2608.00927 AgriJetsonBench (abstract figures)
2026-08-02 (published)

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

speech-to-text

◌

No published speech-to-text results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or NVIDIA Jetson Orin Nano Super 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 AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or NVIDIA Jetson Orin Nano Super 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.