AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) vs Intel Core Ultra 9 288V

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.

No licensed photo available — placeholder drawing.

AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) is faster in all 4 like-for-like comparisons (largest gap: image classification, 15.53×).

	AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)	Intel Core Ultra 9 288V
Best object detection	6100 FPS D Older data (2023)	527 FPS D undated
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	2 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
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)
Intel Core Ultra 9 288V	52.88 FPS throughput (OpenVINO benchmark_app) · b=unknown	ssd-resnet34-1200 INT8 · OpenVINO 2026.4.1 · mid-size CNN	D	unknown power n/a no power published	OpenVINO official performance benchmarks (graph-data-ov.json) undated

✓ 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)
Intel Core Ultra 9 288V	527 FPS throughput (OpenVINO benchmark_app) · b=unknown	yolo_v8n FP16 · OpenVINO 2026.4.1 · unknown	D	unknown power n/a no power published	OpenVINO official performance benchmarks (graph-data-ov.json) undated

instance segmentation

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No published instance segmentation results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or Intel Core Ultra 9 288V 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) · unknown	D	75.00 W spec reported in result source — spec	Vitis AI 3.5 Model Zoo performance table Older data (2023)

Intel Core Ultra 9 288V:

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No published pose estimation results for Intel Core Ultra 9 288V 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

✓ 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)
Intel Core Ultra 9 288V	1981 FPS throughput (OpenVINO benchmark_app) · b=unknown	resnet-50 INT8 · OpenVINO 2026.4.1 · mid-size CNN	D	unknown power n/a no power published	OpenVINO official performance benchmarks (graph-data-ov.json) undated

✓ 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)
Intel Core Ultra 9 288V	4065 FPS throughput (OpenVINO benchmark_app) · b=unknown	mobilenet-v2 INT8 · OpenVINO 2026.4.1 · mobile-class CNN	D	unknown power n/a no power published	OpenVINO official performance benchmarks (graph-data-ov.json) undated

semantic segmentation

Only AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) has published semantic segmentation results.

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)

Intel Core Ultra 9 288V:

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No published semantic segmentation results for Intel Core Ultra 9 288V 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.

speech-to-text

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No published speech-to-text results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or Intel Core Ultra 9 288V 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 Intel Core Ultra 9 288V 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.