AMD Kria KV260 Vision AI Starter Kit (K26 SOM) vs Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)

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.

AMDSOM starter kit (adaptive SoC)No licensed photo yet

MicrochipFPGA SoC (edge)No licensed photo yet

Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) is faster in all 2 like-for-like comparisons (largest gap: object detection, 2.49×).

	AMD Kria KV260 Vision AI Starter Kit (K26 SOM)	Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)
Best object detection	276 FPS D Older data (2023)	66.21 FPS D 2026-09-11 (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	5 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 nano (YOLO-n), batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)	66.21 FPS inference_time · b=1	yolov5n_512x288 INT8 (VNNX) · VectorBlox SDK (VNNX), no compression · nano (YOLO-n)	D	unknown power n/a no power published	Microchip VectorBlox SDK tutorial metrics 2026-09-11 (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)

✓ Like-for-like: model-size class small (YOLO-s), batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)	30.35 FPS inference_time · b=1	yolov9s_70s_15p_512x288 INT8 (VNNX) · VectorBlox SDK (VNNX), unstructured compression · small (YOLO-s)	D	unknown power n/a no power published	Microchip VectorBlox SDK tutorial metrics 2026-09-11 (page last edited)
AMD Kria KV260 Vision AI Starter Kit (K26 SOM)	12.20 FPS throughput (DPU only) · b=1	YOLOv8s-Ghost-P2 (Hard-Swish, xView3-SAR) INT8 (Vitis AI quantizer, power-of-two) · Vitis AI 3.5 VART, DPU inference only, 2 threads · small (YOLO-s)	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)

instance segmentation

Only Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) has published instance segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)	14.13 FPS inference_time · b=1	yolov8n-seg INT8 (VNNX) · VectorBlox SDK (VNNX), no compression · nano (YOLO-n)	D	unknown power n/a no power published	Microchip VectorBlox SDK tutorial metrics 2026-09-11 (page last edited)

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

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No published instance segmentation results for AMD Kria KV260 Vision AI Starter Kit (K26 SOM) or Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

pose estimation

⚠ MIXED COMPARISON — not like-for-like. Baseline nano (YOLO-n) at batch 1. Differs: model-size class mobile-class CNN vs nano (YOLO-n); batch unknown vs 1.

Platform	Result	Model · precision · stack	Grade	Power	Source
Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)	64.49 FPS inference_time · b=1	yolov8n_pose_50s_25p_512x288_split INT8 (VNNX) · VectorBlox SDK (VNNX), unstructured compression · nano (YOLO-n)	D	unknown power n/a no power published	Microchip VectorBlox SDK tutorial metrics 2026-09-11 (page last edited)
AMD Kria KV260 Vision AI Starter Kit (K26 SOM) MIXED: model-size class mobile-class CNN vs nano (YOLO-n); batch unknown vs 1	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)

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

image classification

⚠ MIXED COMPARISON — not like-for-like. Baseline mid-size CNN at batch 1. Differs: model-size class mobile-class CNN vs mid-size CNN; batch unknown vs 1.

Platform	Result	Model · precision · stack	Grade	Power	Source
Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)	68.35 FPS inference_time · b=1	resnet18_86s_07p INT8 (VNNX) · VectorBlox SDK (VNNX), unstructured compression · mid-size CNN	D	unknown power n/a no power published	Microchip VectorBlox SDK tutorial metrics 2026-09-11 (page last edited)
AMD Kria KV260 Vision AI Starter Kit (K26 SOM) MIXED: model-size class mobile-class CNN vs mid-size CNN; 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	D	7.50 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.

Platform	Result	Model · precision · stack	Grade	Power	Source
Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)	3.88 FPS inference_time · b=1	deeplabv3 INT8 (VNNX) · VectorBlox SDK (VNNX), no compression · mid-size CNN	D	unknown power n/a no power published	Microchip VectorBlox SDK tutorial metrics 2026-09-11 (page last edited)
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	D	7.50 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

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No published speech-to-text results for AMD Kria KV260 Vision AI Starter Kit (K26 SOM) or Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) 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 Kria KV260 Vision AI Starter Kit (K26 SOM) or Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) 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.