AMD Kria KV260 Vision AI Starter Kit (K26 SOM) vs NVIDIA Jetson Orin NX 16GB

NVIDIA Jetson Orin NX 16GB is faster in all 3 like-for-like comparisons (largest gap: image classification, 12.33×).
| AMD Kria KV260 Vision AI Starter Kit (K26 SOM) | NVIDIA Jetson Orin NX 16GB | |
|---|---|---|
| Best object detection | 276 FPS D Older data (2023) | 287 FPS B 2026-10-13 (page last edited) |
| Power | 7.50 W spec | n/a |
| Perf / W | 36.76 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
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson Orin NX 16GB | 287 FPS inference_time · b=1 | YOLO26n INT8 · Ultralytics TensorRT · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics documentation (benchmark table) 2026-10-13 (page last edited) |
| AMD Kria KV260 Vision AI Starter Kit (K26 SOM) | 33.60 FPS throughput (DPU only) · b=1 | YOLOv8n-Ghost (Hard-Swish, xView3-SAR) INT8 (Vitis AI quantizer, power-of-two) · Vitis AI 3.5 VART, DPU inference only, 2 threads · nano (YOLO-n) | C | 7.50 W spec platform spec envelope (not measured with this result) | arXiv 2507.04842v2 (SAR vessel detection on Kria KV260), Table 6 2025-11-17 (published) |
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| 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) |
| AMD Kria KV260 Vision AI Starter Kit (K26 SOM) | 5.41 FPS E2E throughput, multi thread · b=unknown | tf_ssdresnet50v1_fpn_coco_640_640_178.4G INT8 · Vitis AI 3.0 (VART) · mid-size CNN | D | 7.50 W spec reported in result source — spec | Vitis AI 3.0 Model Zoo performance table Older data (2023) |
instance segmentation
No published instance segmentation results for AMD Kria KV260 Vision AI Starter Kit (K26 SOM) 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 Kria KV260 Vision AI Starter Kit (K26 SOM) has published pose estimation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| AMD Kria KV260 Vision AI Starter Kit (K26 SOM) | 352 FPS E2E throughput, multi thread · b=unknown | pt_movenet_coco_192_192_0.5G INT8 · Vitis AI 3.0 (VART) · mobile-class CNN | D | 7.50 W spec reported in result source — spec | Vitis AI 3.0 Model Zoo performance table Older data (2023) |
NVIDIA Jetson Orin NX 16GB:
No published pose estimation results for NVIDIA Jetson Orin NX 16GB or AMD Kria KV260 Vision AI Starter Kit (K26 SOM) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
image classification
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| 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) |
| AMD Kria KV260 Vision AI Starter Kit (K26 SOM) | 214 FPS E2E throughput, multi thread · b=unknown | pt_OFA-resnet50_imagenet_160_160_0.88_1.8G INT8 · Vitis AI 3.0 (VART) · mid-size CNN | D | 7.50 W spec reported in result source — spec | Vitis AI 3.0 Model Zoo performance table Older data (2023) |
semantic segmentation
Only AMD Kria KV260 Vision AI Starter Kit (K26 SOM) has published semantic segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| AMD Kria KV260 Vision AI Starter Kit (K26 SOM) | 32.90 FPS E2E throughput, multi thread · b=unknown | pt_SemanticFPN-mobilenetv2_cityscapes_512_1024_10G INT8 · Vitis AI 3.0 (VART) · mobile-class CNN | D | 7.50 W spec reported in result source — spec | Vitis AI 3.0 Model Zoo performance table Older data (2023) |
NVIDIA Jetson Orin NX 16GB:
No published semantic segmentation results for NVIDIA Jetson Orin NX 16GB or AMD Kria KV260 Vision AI Starter Kit (K26 SOM) 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 Kria KV260 Vision AI Starter Kit (K26 SOM):
No published speech-to-text results for AMD Kria KV260 Vision AI Starter Kit (K26 SOM) 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 Kria KV260 Vision AI Starter Kit (K26 SOM):
No published LLM generation results for AMD Kria KV260 Vision AI Starter Kit (K26 SOM) 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
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.