AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) vs NVIDIA Jetson Orin NX 16GB

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

NVIDIA Jetson Orin NX module seated on a carrier motherboard, close-up at Computex 2025 — NVIDIA Jetson Orin NX module on a carrier board. Photo: 4300streetcar, CC BY 4.0, via Wikimedia Commons.

AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) is faster in all 2 like-for-like comparisons (largest gap: image classification, 2.95×).

	AMD Alveo V70 (Versal AI Core, XDNA AIE-ML)	NVIDIA Jetson Orin NX 16GB
Best object detection	6100 FPS D Older data (2023)	287 FPS B 2026-10-13 (page last edited)
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 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)
NVIDIA Jetson Orin NX 16GB	66.50 FPS throughput_offline · b=unknown	MLPerf Retinanet INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · mid-size CNN	D	unknown power n/a no power published	NVIDIA Jetson Benchmarks (MLPerf v3.1 results table) Older data (2023)

instance segmentation

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No published instance segmentation results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or NVIDIA Jetson Orin NX 16GB 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)

NVIDIA Jetson Orin NX 16GB:

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No published pose estimation results for NVIDIA Jetson Orin NX 16GB 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)
NVIDIA Jetson Orin NX 16GB	2641 FPS throughput_offline · b=unknown	MLPerf ResNet INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · mid-size CNN	D	unknown power n/a no power published	NVIDIA Jetson Benchmarks (MLPerf v3.1 results table) Older data (2023)

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)

NVIDIA Jetson Orin NX 16GB:

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No published semantic segmentation results for NVIDIA Jetson Orin NX 16GB 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

Only NVIDIA Jetson Orin NX 16GB has published speech-to-text results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson Orin NX 16GB	432 FPS throughput_offline · b=unknown	MLPerf RNN-T INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · RNN-T	D	unknown power n/a no power published	NVIDIA Jetson Benchmarks (MLPerf v3.1 results table) Older data (2023)

AMD Alveo V70 (Versal AI Core, XDNA AIE-ML):

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No published speech-to-text results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or NVIDIA Jetson Orin NX 16GB yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

LLM generation

Only NVIDIA Jetson Orin NX 16GB has published LLM generation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson Orin NX 16GB	11.00 tok/s generation_throughput · b=1	Nemotron Nano 9B V2 W4A16 · vLLM · LLM 5–14B	C	unknown power n/a no power published	NVIDIA Jetson AI Lab benchmarks (benchmarks.json) 2026-07-21 (page last edited)

AMD Alveo V70 (Versal AI Core, XDNA AIE-ML):

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No published LLM generation results for AMD Alveo V70 (Versal AI Core, XDNA AIE-ML) or NVIDIA Jetson Orin NX 16GB 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.