AMD Zynq UltraScale+ ZCU102 (ZU9EG) vs NVIDIA Jetson AGX Orin 64GB

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 licensed photo available — placeholder drawing.

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.

NVIDIA Jetson AGX Orin 64GB is faster in all 2 like-for-like comparisons (largest gap: object detection, 20.79×).

	AMD Zynq UltraScale+ ZCU102 (ZU9EG)	NVIDIA Jetson AGX Orin 64GB
Best object detection	539 FPS D Older data (2023)	435 FPS B undated
Power	n/a	65.00 W spec
Perf / W	n/a	6.69 FPS/W spec
Price	n/a	$1999 list
Workloads with data	4 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 mid-size CNN, batch unknown (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	149 FPS throughput_offline · b=unknown	MLPerf Retinanet 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) 2026-10
AMD Zynq UltraScale+ ZCU102 (ZU9EG)	7.15 FPS E2E throughput, multi thread · b=unknown	tf_mlperf_resnet34_coco_1200_1200_433G INT8 · Vitis AI 3.0 (VART) · mid-size CNN	D	unknown power n/a no power published	Vitis AI 3.0 Model Zoo performance table Older data (2023)

instance segmentation

◌

No published instance segmentation results for AMD Zynq UltraScale+ ZCU102 (ZU9EG) 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.

pose estimation

Only AMD Zynq UltraScale+ ZCU102 (ZU9EG) has published pose estimation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Zynq UltraScale+ ZCU102 (ZU9EG)	391 FPS E2E throughput, multi thread · b=unknown	pt_movenet_coco_192_192_0.5G INT8 · Vitis AI 3.0 (VART) · unknown	D	unknown power n/a no power published	Vitis AI 3.0 Model Zoo performance table Older data (2023)

NVIDIA Jetson AGX Orin 64GB:

◌

No published pose estimation results for NVIDIA Jetson AGX Orin 64GB or AMD Zynq UltraScale+ ZCU102 (ZU9EG) 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 mid-size CNN, batch unknown (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	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) 2026-10
AMD Zynq UltraScale+ ZCU102 (ZU9EG)	371 FPS E2E throughput, multi thread · b=unknown	pt_OFA-resnet50_imagenet_160_160_0.88_1.8G INT8 · Vitis AI 3.0 (VART) · mid-size CNN	D	unknown power n/a no power published	Vitis AI 3.0 Model Zoo performance table Older data (2023)

semantic segmentation

Only AMD Zynq UltraScale+ ZCU102 (ZU9EG) has published semantic segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Zynq UltraScale+ ZCU102 (ZU9EG)	437 FPS E2E throughput, multi thread · b=unknown	tf2_2d-unet_nuclei_128_128_5.31G INT8 · Vitis AI 3.0 (VART) · mid-size CNN	D	unknown power n/a no power published	Vitis AI 3.0 Model Zoo performance table Older data (2023)

NVIDIA Jetson AGX Orin 64GB:

◌

No published semantic segmentation results for NVIDIA Jetson AGX Orin 64GB or AMD Zynq UltraScale+ ZCU102 (ZU9EG) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

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) 2026-10

AMD Zynq UltraScale+ ZCU102 (ZU9EG):

◌

No published speech-to-text results for AMD Zynq UltraScale+ ZCU102 (ZU9EG) 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) undated

AMD Zynq UltraScale+ ZCU102 (ZU9EG):

◌

No published LLM generation results for AMD Zynq UltraScale+ ZCU102 (ZU9EG) 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

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.