HWBench

AMD Versal AI Edge Series Gen 2 VEK385 vs NVIDIA Jetson AGX Thor

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 like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.

AMD Versal AI Edge Series Gen 2 VEK385NVIDIA Jetson AGX Thor
Best object detection93.50 FPS D
2026-09-24 (published)
719 FPS B
2026-10-13 (page last edited)
Powern/a130 W spec
Perf / Wn/a5.53 FPS/W spec
Price$15995 list$5499 list
Workloads with data2 of 72 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 nano (YOLO-n) at batch 1. Differs: model-size class medium (YOLO-m) vs nano (YOLO-n).
PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson AGX Thor719 FPS
inference_time · b=1
YOLO26n
FP16 · Ultralytics TensorRT · nano (YOLO-n)
B130 W spec
platform spec envelope (not measured with this result)
Ultralytics documentation (benchmark table)
2026-10-13 (page last edited)
AMD Versal AI Edge Series Gen 2 VEK385
MIXED: model-size class medium (YOLO-m) vs nano (YOLO-n)
93.50 FPS
throughput · b=1
yolov8m
VINT8 with BF16 tail (Quark) · Vitis AI 6.3 VART ml_vart --benchmark --runs 100 · medium (YOLO-m)
Dunknown power n/a
no power published
AMD Vitis AI 6.3 VEK385 YOLOv8m tutorial
2026-09-24 (published)

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

instance segmentation

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No published instance segmentation results for AMD Versal AI Edge Series Gen 2 VEK385 or NVIDIA Jetson AGX Thor yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

pose estimation

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No published pose estimation results for AMD Versal AI Edge Series Gen 2 VEK385 or NVIDIA Jetson AGX Thor yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

image classification

Only AMD Versal AI Edge Series Gen 2 VEK385 has published image classification results.

PlatformResultModel · precision · stackGradePowerSource
AMD Versal AI Edge Series Gen 2 VEK385265 FPS
throughput · b=1
resnet50-v1-12 (ONNX)
INT8 (Quark) · Vitis AI 6.3 ONNX Runtime Vitis AI EP (evaluate.py, Python loop) · mid-size CNN
Dunknown power n/a
no power published
AMD Vitis AI 6.3 VEK385 ResNet50 Quark tutorial
2026-09-23 (page last edited)

NVIDIA Jetson AGX Thor:

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No published image classification results for NVIDIA Jetson AGX Thor or AMD Versal AI Edge Series Gen 2 VEK385 yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

semantic segmentation

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No published semantic segmentation results for AMD Versal AI Edge Series Gen 2 VEK385 or NVIDIA Jetson AGX Thor 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 Versal AI Edge Series Gen 2 VEK385 or NVIDIA Jetson AGX Thor 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 AGX Thor has published LLM generation results.

PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson AGX Thor41.32 tok/s
tok/s gen, concurrency 1 · b=1
Deepseek R1 7B
n/s on page · NVIDIA (vLLM/TensorRT-LLM per page) · LLM 5–14B
D130 W spec
platform spec envelope (not measured with this result)
NVIDIA Jetson Benchmarks
on or before 2025-11-08

AMD Versal AI Edge Series Gen 2 VEK385:

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No published LLM generation results for AMD Versal AI Edge Series Gen 2 VEK385 or NVIDIA Jetson AGX Thor 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.