Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) vs NVIDIA Jetson Orin NX 16GB

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NVIDIA Jetson Orin NX module seated on a carrier motherboard, close-up at Computex 2025 — NVIDIA Jetson Orin NX module on a carrier board. Photo: 4300streetcar, CC BY 4.0, via Wikimedia Commons.

NVIDIA Jetson Orin NX 16GB is faster in the only like-for-like comparison (largest gap: object detection, 4.33×).

	Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)	NVIDIA Jetson Orin NX 16GB
Best object detection	66.21 FPS D 2026-09-11 (page last edited)	287 FPS B 2026-10-13 (page last edited)
Power	n/a	n/a
Perf / W	n/a	n/a
Price	n/a	n/a
Workloads with data	5 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

✓ 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
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)
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)

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)

NVIDIA Jetson Orin NX 16GB:

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No published instance segmentation results for NVIDIA Jetson Orin NX 16GB 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)

NVIDIA Jetson Orin NX 16GB:

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No published pose estimation results for NVIDIA Jetson Orin NX 16GB 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

⚠ 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)	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)
NVIDIA Jetson Orin NX 16GB MIXED: batch unknown vs 1	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)

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

semantic segmentation

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

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)

NVIDIA Jetson Orin NX 16GB:

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No published semantic segmentation results for NVIDIA Jetson Orin NX 16GB 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.

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)

Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox):

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

Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox):

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

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.