AMD Zynq UltraScale+ ZCU102 (ZU9EG) vs AMD Zynq UltraScale+ ZCU104 (ZU7EV)
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.
AMD Zynq UltraScale+ ZCU102 (ZU9EG) is faster in all 12 like-for-like comparisons (largest gap: object detection, 1.36×).
| AMD Zynq UltraScale+ ZCU102 (ZU9EG) | AMD Zynq UltraScale+ ZCU104 (ZU7EV) | |
|---|---|---|
| Best object detection | 539 FPS D Older data (2023) | 463 FPS D Older data (2023) |
| Power | n/a | n/a |
| Perf / W | n/a | n/a |
| Price | n/a | n/a |
| 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 small (YOLO-s), 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 |
|---|---|---|---|---|---|
| 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) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) | 25.43 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) |
✓ Like-for-like: model-size class medium (YOLO-m), 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 |
|---|---|---|---|---|---|
| AMD Zynq UltraScale+ ZCU102 (ZU9EG) | 27.31 FPS E2E throughput, multi thread · b=unknown | pt_yolov6m_coco_640_640_82.4G INT8 · Vitis AI 3.0 (VART) · medium (YOLO-m) | D | unknown power n/a no power published | Vitis AI 3.0 Model Zoo performance table Older data (2023) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) | 24.53 FPS E2E throughput, multi thread · b=unknown | pt_yolov6m_coco_640_640_82.4G INT8 · Vitis AI 3.0 (VART) · medium (YOLO-m) | D | unknown power n/a no power published | Vitis AI 3.0 Model Zoo performance table Older data (2023) |
✓ 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 |
|---|---|---|---|---|---|
| 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) |
| 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) |
✓ Like-for-like: model-size class mobile-class 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 |
|---|---|---|---|---|---|
| AMD Zynq UltraScale+ ZCU102 (ZU9EG) | 365 FPS E2E throughput, multi thread · b=unknown | tf_ssdmobilenetv1_coco_300_300_2.47G 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) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) | 315 FPS E2E throughput, multi thread · b=unknown | tf_ssdmobilenetv1_coco_300_300_2.47G 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) |
✓ Like-for-like: model-size class unknown, 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 |
|---|---|---|---|---|---|
| AMD Zynq UltraScale+ ZCU102 (ZU9EG) | 539 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) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) | 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) |
instance segmentation
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No published instance segmentation results for AMD Zynq UltraScale+ ZCU102 (ZU9EG) 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.
pose estimation
✓ Like-for-like: model-size class unknown, 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 |
|---|---|---|---|---|---|
| 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) |
| 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) · unknown | D | unknown power n/a no power published | Vitis AI 3.0 Model Zoo performance table Older data (2023) |
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 |
|---|---|---|---|---|---|
| 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) |
| 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) |
✓ Like-for-like: model-size class mobile-class 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 |
|---|---|---|---|---|---|
| AMD Zynq UltraScale+ ZCU102 (ZU9EG) | 4832 FPS E2E throughput, multi thread · b=unknown | tf_mobilenetv1_0.25_imagenet_128_128_27M 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) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) | 4325 FPS E2E throughput, multi thread · b=unknown | tf_mobilenetv1_0.25_imagenet_128_128_27M 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) |
✓ Like-for-like: model-size class unknown, 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 |
|---|---|---|---|---|---|
| AMD Zynq UltraScale+ ZCU102 (ZU9EG) | 1551 FPS E2E throughput, multi thread · b=unknown | pt_squeezenet_imagenet_224_224_703.5M 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) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) | 1326 FPS E2E throughput, multi thread · b=unknown | pt_squeezenet_imagenet_224_224_703.5M 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) |
semantic segmentation
✓ 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 |
|---|---|---|---|---|---|
| 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) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) | 352 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) |
✓ Like-for-like: model-size class mobile-class 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 |
|---|---|---|---|---|---|
| AMD Zynq UltraScale+ ZCU102 (ZU9EG) | 54.75 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) |
| 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) |
✓ Like-for-like: model-size class unknown, 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 |
|---|---|---|---|---|---|
| AMD Zynq UltraScale+ ZCU102 (ZU9EG) | 188 FPS E2E throughput, multi thread · b=unknown | pt_CFLOW_LIDC_128_128_10.42G 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) |
| AMD Zynq UltraScale+ ZCU104 (ZU7EV) | 145 FPS E2E throughput, multi thread · b=unknown | pt_CFLOW_LIDC_128_128_10.42G 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) |
speech-to-text
◌
No published speech-to-text results for AMD Zynq UltraScale+ ZCU102 (ZU9EG) 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.
LLM generation
◌
No published LLM generation results for AMD Zynq UltraScale+ ZCU102 (ZU9EG) 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.
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.