MemryX MX3 M.2 module vs Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)

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MemryX MX3 M.2 module is faster in all 5 like-for-like comparisons (largest gap: semantic segmentation, 195×).

	MemryX MX3 M.2 module	Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
Best object detection	8519 FPS C 2026-07-15 (published)	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
MemryX MX3 M.2 module	8519 FPS throughput · b=1	Malaria-Detector not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · unknown	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)
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)

instance segmentation

Only MemryX MX3 M.2 module has published instance segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
MemryX MX3 M.2 module	1023 FPS throughput · b=1	YOLO26-nano-seg not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · unknown	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)

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 MemryX MX3 M.2 module 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 MemryX MX3 M.2 module has published pose estimation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
MemryX MX3 M.2 module	2721 FPS throughput · b=1	MoveNet.SinglePose.Lightning not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mobile-class CNN	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)

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 MemryX MX3 M.2 module 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 mobile-class CNN, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
MemryX MX3 M.2 module	8312 FPS throughput · b=1	MobileNet not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mobile-class CNN	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)
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)

✓ 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
MemryX MX3 M.2 module	2317 FPS throughput · b=1	ResNet-50 (MXA-Optimized) not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mid-size CNN	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)
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)

✓ 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
MemryX MX3 M.2 module	10057 FPS throughput · b=1	Vehicle-Attributes-recog-barrier-0039 not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · unknown	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)
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)

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
MemryX MX3 M.2 module	1998 FPS throughput · b=1	Deeplab-v3 not stated (MX3 activations BF16 / weights 4-8-16 bit per vendor) · MemryX SDK 2.2 (closed-loop compiled DFP) · mid-size CNN	C	unknown power n/a no power published	MemryX Model Explorer (SDK 2.2) 2026-07-15 (published)
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)

speech-to-text

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No published speech-to-text results for MemryX MX3 M.2 module 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 MemryX MX3 M.2 module 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.