AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) vs Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)

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.

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

	AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)	Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
Best object detection	6100 FPS D Older data (2023)	117 FPS D 2026-08-10 (published)
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	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 small (YOLO-s) at batch 14. Differs: model-size class unknown vs small (YOLO-s); batch 1 vs 14.

Platform	Result	Model · precision · stack	Grade	Power	Source
AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)	85.28 FPS E2E throughput, multi thread · b=14	yolov5s6_pt INT8 · Vitis AI 3.5 Library (VART), batch 14 DPU · small (YOLO-s)	D	75.00 W spec platform spec envelope (not measured with this result)	AMD UG1354 Vitis AI Library performance tables undated
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) MIXED: model-size class unknown vs small (YOLO-s); batch 1 vs 14	117 FPS throughput · b=1	yolo-v3-tiny-tf FP16 · FPGA AI Suite 2026.1.1 / OpenVINO; IP throughput (hostless) · unknown	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)

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

instance segmentation

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No published instance segmentation results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) 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 Alveo V70 (Versal AI Core, XDNA AIE-ML) has published pose estimation results.

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)

Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite):

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No published pose estimation results for Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) or AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

image classification

⚠ 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
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)	1391 FPS throughput · b=1	mobilenet-v1-1.0-224 not stated in table (set by .arch file) · FPGA AI Suite 2026.1.1 / OpenVINO; IP throughput (hostless) · mobile-class CNN	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)
AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) MIXED: batch unknown vs 1	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)

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
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)	10.26 FPS throughput · b=1	unet-camvid-onnx-0001 not stated in table (set by .arch file) · FPGA AI Suite 2026.1.1 / OpenVINO; IP throughput (hostless) · mid-size CNN	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)
AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) MIXED: batch unknown vs 1	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)

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 Alveo V70 (Versal AI Core, XDNA AIE-ML) or Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) 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 Alveo V70 (Versal AI Core, XDNA AIE-ML) or Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) 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.