AMD Zynq UltraScale+ ZCU104 (ZU7EV) 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.

AMDeval kit (adaptive SoC)No licensed photo yet

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.

Showing the newest results per platform and source. 12 superseded older results are hidden.Showing all results, including 12 superseded by newer results from the same source.

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+ ZCU104 (ZU7EV)	NVIDIA Jetson AGX Orin 64GB
Best object detection	463 FPS D Older data (2023)	435 FPS B 2026-10-13 (page last edited)
Power	n/a	65.00 W spec
Perf / W	n/a	6.69 FPS/W spec
Price	n/a	$3499 list
Workloads with data	4 of 7	3 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 unknown vs nano (YOLO-n); batch unknown vs 1.

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)
AMD Zynq UltraScale+ ZCU104 (ZU7EV) MIXED: model-size class unknown vs nano (YOLO-n); batch unknown vs 1	463 FPS E2E throughput, multi thread · b=unknown	pt_yolox-nano_coco_416_416_1G 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)

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

instance segmentation

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No published instance segmentation results for AMD Zynq UltraScale+ ZCU104 (ZU7EV) 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+ ZCU104 (ZU7EV) has published pose estimation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Zynq UltraScale+ ZCU104 (ZU7EV)	372 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 AGX Orin 64GB:

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No published pose estimation results for NVIDIA Jetson AGX Orin 64GB or AMD Zynq UltraScale+ ZCU104 (ZU7EV) 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+ ZCU104 (ZU7EV) has published image classification results.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Zynq UltraScale+ ZCU104 (ZU7EV)	354 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 AGX Orin 64GB:

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No published image classification results for NVIDIA Jetson AGX Orin 64GB or AMD Zynq UltraScale+ ZCU104 (ZU7EV) 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 mobile-class CNN at batch unknown. Differs: model-size class unknown vs mobile-class CNN; batch 1 vs unknown.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Zynq UltraScale+ ZCU104 (ZU7EV)	53.02 FPS E2E throughput, multi thread · b=unknown	pt_SemanticFPN-mobilenetv2_cityscapes_512_1024_10G 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 AGX Orin 64GB MIXED: model-size class unknown vs mobile-class CNN; batch 1 vs unknown	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)

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

speech-to-text

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No published speech-to-text results for AMD Zynq UltraScale+ ZCU104 (ZU7EV) 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)

AMD Zynq UltraScale+ ZCU104 (ZU7EV):

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No published LLM generation results for AMD Zynq UltraScale+ ZCU104 (ZU7EV) 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 2 like-for-like comparisons (largest gap: object detection, 28.26×).

	AMD Zynq UltraScale+ ZCU104 (ZU7EV)	NVIDIA Jetson AGX Orin 64GB
Best object detection	463 FPS D Older data (2023)	435 FPS B 2026-10-13 (page last edited)
Power	n/a	65.00 W spec
Perf / W	n/a	6.69 FPS/W spec
Price	n/a	$3499 list
Workloads with data	4 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

✓ 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) Older data (2023)
AMD Zynq UltraScale+ ZCU104 (ZU7EV)	5.26 FPS E2E throughput, multi thread · b=unknown	tf_ssdresnet50v1_fpn_coco_640_640_178.4G 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

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pose estimation

Only AMD Zynq UltraScale+ ZCU104 (ZU7EV) has published pose estimation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Zynq UltraScale+ ZCU104 (ZU7EV)	372 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 AGX Orin 64GB:

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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) Older data (2023)
AMD Zynq UltraScale+ ZCU104 (ZU7EV)	354 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

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

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Zynq UltraScale+ ZCU104 (ZU7EV)	53.02 FPS E2E throughput, multi thread · b=unknown	pt_SemanticFPN-mobilenetv2_cityscapes_512_1024_10G 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 AGX Orin 64GB MIXED: model-size class unknown vs mobile-class CNN; batch 1 vs unknown	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)

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

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)

AMD Zynq UltraScale+ ZCU104 (ZU7EV):

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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)

AMD Zynq UltraScale+ ZCU104 (ZU7EV):

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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.