AMD Zynq UltraScale+ ZCU104 (ZU7EV) vs MemryX MX3 M.2 module

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

MemryXedge accelerator cardNo 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+ ZCU104 (ZU7EV)	MemryX MX3 M.2 module
Best object detection	463 FPS D Older data (2023)	8519 FPS C 2026-07-15 (published)
Power	n/a	n/a
Perf / W	n/a	n/a
Price	n/a	n/a
Workloads with data	4 of 7	5 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 mobile-class CNN at batch 1. Differs: model-size class unknown vs mobile-class CNN; batch unknown vs 1.

Platform	Result	Model · precision · stack	Grade	Power	Source
MemryX MX3 M.2 module	2391 FPS throughput · b=1	MediaPipe-object-Detection-3d-camera not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mobile-class CNN	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)
AMD Zynq UltraScale+ ZCU104 (ZU7EV) MIXED: model-size class unknown vs mobile-class CNN; 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

Only MemryX MX3 M.2 module has published instance segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
MemryX MX3 M.2 module	1023 FPS throughput · b=1	YOLO26-nano-seg not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · unknown	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)

AMD Zynq UltraScale+ ZCU104 (ZU7EV):

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No published instance segmentation results for AMD Zynq UltraScale+ ZCU104 (ZU7EV) or MemryX MX3 M.2 module yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

pose estimation

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

Platform	Result	Model · precision · stack	Grade	Power	Source
MemryX MX3 M.2 module	2721 FPS throughput · b=1	MoveNet.SinglePose.Lightning not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mobile-class CNN	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)
AMD Zynq UltraScale+ ZCU104 (ZU7EV) MIXED: batch unknown vs 1	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)

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

image classification

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

Platform	Result	Model · precision · stack	Grade	Power	Source
MemryX MX3 M.2 module	2317 FPS throughput · b=1	ResNet-50 (MXA-Optimized) not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mid-size CNN	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)
AMD Zynq UltraScale+ ZCU104 (ZU7EV) MIXED: model-size class mobile-class CNN vs mid-size CNN; batch unknown vs 1	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)

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

semantic segmentation

⚠ MIXED COMPARISON — not like-for-like. Baseline mid-size CNN at batch 1. Differs: batch unknown vs 1.

Platform	Result	Model · precision · stack	Grade	Power	Source
MemryX MX3 M.2 module	1998 FPS throughput · b=1	Deeplab-v3 not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mid-size CNN	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)
AMD Zynq UltraScale+ ZCU104 (ZU7EV) MIXED: batch unknown vs 1	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)

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 MemryX MX3 M.2 module yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

LLM generation

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No published LLM generation results for AMD Zynq UltraScale+ ZCU104 (ZU7EV) or MemryX MX3 M.2 module 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.