HWBench

AMD Kria KV260 Vision AI Starter Kit (K26 SOM) 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.

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

AMD Kria KV260 Vision AI Starter Kit (K26 SOM)Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
Best object detection276 FPS D
Older data (2023)
117 FPS D
2026-08-10 (published)
Power7.50 W specn/a
Perf / W36.76 FPS/W specn/a
Pricen/an/a
Workloads with data4 of 73 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 unknown vs nano (YOLO-n).
PlatformResultModel · precision · stackGradePowerSource
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)
C7.50 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)
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
MIXED: model-size class unknown vs nano (YOLO-n)
117 FPS
throughput · b=1
yolo-v3-tiny-tf
FP16 · FPGA AI Suite 2026.1.1 / OpenVINO; IP throughput (hostless) · unknown
Dunknown 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

◌

No published instance segmentation results for AMD Kria KV260 Vision AI Starter Kit (K26 SOM) 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 Kria KV260 Vision AI Starter Kit (K26 SOM) has published pose estimation results.

PlatformResultModel · precision · stackGradePowerSource
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
D7.50 W spec
reported in result source — spec
Vitis AI 3.0 Model Zoo performance table
Older data (2023)

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

◌

No published pose estimation results for Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) 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

⚠ MIXED COMPARISON — not like-for-like. Baseline mobile-class CNN at batch 1. Differs: batch unknown vs 1.
PlatformResultModel · precision · stackGradePowerSource
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
Dunknown power n/a
no power published
Altera FPGA AI Suite Handbook (performance tables)
2026-08-10 (published)
AMD Kria KV260 Vision AI Starter Kit (K26 SOM)
MIXED: batch unknown vs 1
2432 FPS
E2E throughput, multi thread · b=unknown
tf_mobilenetv1_0.25_imagenet_128_128_27M
INT8 · Vitis AI 3.0 (VART) · mobile-class CNN
D7.50 W spec
reported in result source — spec
Vitis AI 3.0 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.
PlatformResultModel · precision · stackGradePowerSource
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
Dunknown power n/a
no power published
Altera FPGA AI Suite Handbook (performance tables)
2026-08-10 (published)
AMD Kria KV260 Vision AI Starter Kit (K26 SOM)
MIXED: batch unknown vs 1
183 FPS
E2E throughput, multi thread · b=unknown
tf2_2d-unet_nuclei_128_128_5.31G
INT8 · Vitis AI 3.0 (VART) · mid-size CNN
D7.50 W spec
reported in result source — spec
Vitis AI 3.0 Model Zoo performance table
Older data (2023)

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

speech-to-text

◌

No published speech-to-text results for AMD Kria KV260 Vision AI Starter Kit (K26 SOM) 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

◌

No published LLM generation results for AMD Kria KV260 Vision AI Starter Kit (K26 SOM) 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.