AMD Zynq UltraScale+ ZCU102 (ZU9EG) vs NVIDIA Jetson Thor T4000

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.

AMDeval kit (adaptive SoC)No licensed photo yet

NVIDIAedge moduleNo licensed photo yet

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

	AMD Zynq UltraScale+ ZCU102 (ZU9EG)	NVIDIA Jetson Thor T4000
Best object detection	539 FPS D Older data (2023)	n/a
Power	n/a	n/a
Perf / W	n/a	n/a
Price	n/a	n/a
Workloads with data	4 of 7	1 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

Only AMD Zynq UltraScale+ ZCU102 (ZU9EG) has published object detection results.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Zynq UltraScale+ ZCU102 (ZU9EG)	26.09 FPS E2E throughput, multi thread · b=unknown	pt_yolov5s6_coco_1280_1280_17G INT8 · Vitis AI 3.0 (VART) · small (YOLO-s)	D	unknown power n/a no power published	Vitis AI 3.0 Model Zoo performance table Older data (2023)

NVIDIA Jetson Thor T4000:

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No published object detection results for NVIDIA Jetson Thor T4000 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.

instance segmentation

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No published instance segmentation results for AMD Zynq UltraScale+ ZCU102 (ZU9EG) or NVIDIA Jetson Thor T4000 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) · mobile-class CNN	D	unknown power n/a no power published	Vitis AI 3.0 Model Zoo performance table Older data (2023)

NVIDIA Jetson Thor T4000:

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No published pose estimation results for NVIDIA Jetson Thor T4000 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

Only AMD Zynq UltraScale+ ZCU102 (ZU9EG) has published image classification results.

Platform	Result	Model · precision · stack	Grade	Power	Source
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)

NVIDIA Jetson Thor T4000:

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No published image classification results for NVIDIA Jetson Thor T4000 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.

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 Thor T4000:

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No published semantic segmentation results for NVIDIA Jetson Thor T4000 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

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No published speech-to-text results for AMD Zynq UltraScale+ ZCU102 (ZU9EG) or NVIDIA Jetson Thor T4000 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 Thor T4000 has published LLM generation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson Thor T4000	35.00 tok/s generation_throughput · b=1	Qwen 3 8B NVFP4 · vLLM · LLM 5–14B	C	unknown power n/a no power published	NVIDIA Jetson AI Lab benchmarks (benchmarks.json) 2026-07-21 (page last edited)

AMD Zynq UltraScale+ ZCU102 (ZU9EG):

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No published LLM generation results for AMD Zynq UltraScale+ ZCU102 (ZU9EG) or NVIDIA Jetson Thor T4000 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.