AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) vs AMD Zynq UltraScale+ ZCU102 (ZU9EG)
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.
AMDPCIe accelerator cardNo licensed photo yet
AMDeval kit (adaptive SoC)No licensed photo yet
Split result: AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) is faster in 9 and AMD Zynq UltraScale+ ZCU102 (ZU9EG) in 1 of 10 like-for-like comparisons.
| AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) | AMD Zynq UltraScale+ ZCU102 (ZU9EG) | |
|---|---|---|
| Best object detection | 6100 FPS D Older data (2023) | 539 FPS D Older data (2023) |
| Power | 75.00 W spec | n/a |
| Perf / W | 81.34 FPS/W spec | 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 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 Alveo V70 (Versal AI Core, XDNA AIE-ML) | 280 FPS E2E throughput, multi thread · b=unknown | pt_yolov6m_3.5 INT8 · Vitis AI 3.5 (VART) · medium (YOLO-m) | D | 75.00 W spec reported in result source — spec | Vitis AI 3.5 Model Zoo performance table Older data (2023) |
| 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) |
✓ 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 Alveo V70 (Versal AI Core, XDNA AIE-ML) | 70.16 FPS E2E throughput, multi thread · b=unknown | tf_mlperf_resnet34_3.5 INT8 · Vitis AI 3.5 (VART) · mid-size CNN | D | 75.00 W spec reported in result source — spec | Vitis AI 3.5 Model Zoo performance table Older data (2023) |
| 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) |
✓ 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 Alveo V70 (Versal AI Core, XDNA AIE-ML) | 6100 FPS E2E throughput, multi thread · b=unknown | tf_ssdmobilenetv1_3.5 INT8 · Vitis AI 3.5 (VART) · mobile-class CNN | D | 75.00 W spec reported in result source — spec | Vitis AI 3.5 Model Zoo performance table Older data (2023) |
| 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) |
✓ 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 Alveo V70 (Versal AI Core, XDNA AIE-ML) | 2174 FPS E2E throughput, multi thread · b=unknown | pt_face-mask-detection_3.5 INT8 · Vitis AI 3.5 (VART) · unknown | D | 75.00 W spec reported in result source — spec | Vitis AI 3.5 Model Zoo performance table Older data (2023) |
| 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) |
instance segmentation
◌
No published instance segmentation results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) 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.
pose estimation
✓ 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 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 | D | 75.00 W spec reported in result source — spec | Vitis AI 3.5 Model Zoo performance table Older data (2023) |
| 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) |
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 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 | D | 75.00 W spec reported in result source — spec | Vitis AI 3.5 Model Zoo performance table Older data (2023) |
| 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) |
✓ 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 Alveo V70 (Versal AI Core, XDNA AIE-ML) | 63109 FPS E2E throughput, multi thread · b=unknown | tf_mobilenetv1-0.25_3.5 INT8 · Vitis AI 3.5 (VART) · mobile-class CNN | D | 75.00 W spec reported in result source — spec | Vitis AI 3.5 Model Zoo performance table Older data (2023) |
| 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) |
✓ 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 Alveo V70 (Versal AI Core, XDNA AIE-ML) | 12926 FPS E2E throughput, multi thread · b=unknown | pt_OFA-depthwise-res50_3.5 INT8 · Vitis AI 3.5 (VART) · unknown | D | 75.00 W spec reported in result source — spec | Vitis AI 3.5 Model Zoo performance table Older data (2023) |
| 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) |
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 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 | D | 75.00 W spec reported in result source — spec | Vitis AI 3.5 Model Zoo performance table Older data (2023) |
| 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) |
✓ 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 Alveo V70 (Versal AI Core, XDNA AIE-ML) | 187 FPS E2E throughput, multi thread · b=unknown | pt_pointpillars_3.5 INT8 · Vitis AI 3.5 (VART) · unknown | D | 75.00 W spec reported in result source — spec | Vitis AI 3.5 Model Zoo performance table Older data (2023) |
speech-to-text
◌
No published speech-to-text results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) 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.
LLM generation
◌
No published LLM generation results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) 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.
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.