Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) vs Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)

MicrochipFPGA SoC (edge)No licensed photo yet

AlteraFPGA (PCIe/dev kit)No licensed photo yet

Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) is faster in all 5 like-for-like comparisons (largest gap: image classification, 12.91×).

	Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)	Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
Best object detection	66.21 FPS D 2026-09-11 (page last edited)	117 FPS D 2026-08-10 (published)
Power	n/a	n/a
Perf / W	n/a	n/a
Price	n/a	n/a
Workloads with data	5 of 7	3 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 unknown, batch 1 (size or batch not stated by source — unverified). Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)	117 FPS throughput · b=1	yolo-v3-tiny-tf FP16 · FPGA AI Suite 2026.1.1 / OpenVINO; IP throughput (hostless) · unknown	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)
Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)	58.05 FPS inference_time · b=1	132_YOLOX INT8 (VNNX) · VectorBlox SDK (VNNX), no compression · unknown	D	unknown power n/a no power published	Microchip VectorBlox SDK tutorial metrics 2026-09-11 (page last edited)

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)

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

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

Only Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) has published pose estimation results.

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)

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

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

image classification

✓ Like-for-like: model-size class mid-size CNN, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)	220 FPS throughput · b=1	resnet-50-tf not stated in table (set by .arch file) · FPGA AI Suite 2026.1.1 / OpenVINO; IP throughput (hostless) · mid-size CNN	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)
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)

✓ Like-for-like: model-size class mobile-class CNN, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
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	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)
Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)	672 FPS inference_time · b=1	mobilenet-v1-0.25-128 INT8 (VNNX) · VectorBlox SDK (VNNX), no compression · mobile-class CNN	D	unknown power n/a no power published	Microchip VectorBlox SDK tutorial metrics 2026-09-11 (page last edited)

✓ Like-for-like: model-size class unknown, batch 1 (size or batch not stated by source — unverified). Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)	1289 FPS throughput · b=1	yolo-v8-nano classification not stated in table (set by .arch file) · FPGA AI Suite 2026.1.1 / OpenVINO; IP throughput (hostless) · unknown	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)
Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)	99.88 FPS inference_time · b=1	onnx_squeezenet1.1 INT8 (VNNX) · VectorBlox SDK (VNNX), no compression · unknown	D	unknown power n/a no power published	Microchip VectorBlox SDK tutorial metrics 2026-09-11 (page last edited)

semantic segmentation

✓ Like-for-like: model-size class mid-size CNN, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
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	D	unknown power n/a no power published	Altera FPGA AI Suite Handbook (performance tables) 2026-08-10 (published)
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)

speech-to-text

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No published speech-to-text results for Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) 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

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No published LLM generation results for Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) 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.