Axelera Metis Embedded 113m M.2 card vs Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)

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Axelera Metis Embedded 113m M.2 card is faster in all 4 like-for-like comparisons (largest gap: image classification, 20.05×).

	Axelera Metis Embedded 113m M.2 card	Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
Best object detection	3004 FPS C 2026-10-15 (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
Axelera Metis Embedded 113m M.2 card	1337 FPS throughput · b=1	YOLOv7-tiny INT8 · Voyager SDK (GStreamer pipeline) · unknown	C	unknown power n/a no power published	Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited)
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 Axelera Metis Embedded 113m M.2 card has published instance segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Axelera Metis Embedded 113m M.2 card	186 FPS throughput · b=1	YOLACT-ResNet50 INT8 · Voyager SDK (GStreamer pipeline) · mid-size CNN	C	unknown power n/a no power published	Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (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 Axelera Metis Embedded 113m M.2 card 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 Axelera Metis Embedded 113m M.2 card has published pose estimation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Axelera Metis Embedded 113m M.2 card	746 FPS throughput · b=1	YOLOv8n-pose INT8 · Voyager SDK (GStreamer pipeline) · nano (YOLO-n)	C	unknown power n/a no power published	Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (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 Axelera Metis Embedded 113m M.2 card 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
Axelera Metis Embedded 113m M.2 card	4257 FPS throughput · b=1	MobileNetV4-small INT8 · Voyager SDK (GStreamer pipeline) · mobile-class CNN	C	unknown power n/a no power published	Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited)
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
Axelera Metis Embedded 113m M.2 card	4412 FPS throughput · b=1	ResNet-10t INT8 · Voyager SDK (GStreamer pipeline) · mid-size CNN	C	unknown power n/a no power published	Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited)
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
Axelera Metis Embedded 113m M.2 card	5881 FPS throughput · b=1	SqueezeNet 1.1 INT8 · Voyager SDK (GStreamer pipeline) · unknown	C	unknown power n/a no power published	Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited)
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

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

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)
Axelera Metis Embedded 113m M.2 card MIXED: model-size class nano (YOLO-n) vs mid-size CNN	294 FPS throughput · b=1	YOLO26n-sem INT8 · Voyager SDK (GStreamer pipeline) · nano (YOLO-n)	C	unknown power n/a no power published	Axelera Voyager SDK model zoo (docs/reference/models/model-zoo.md) 2026-10-15 (page last edited)

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

speech-to-text

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No published speech-to-text results for Axelera Metis Embedded 113m M.2 card 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 Axelera Metis Embedded 113m M.2 card 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.