NVIDIA Jetson AGX Orin 64GB vs Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)

NVIDIA Jetson AGX Orin developer kit with its retail box, on a black background — NVIDIA Jetson AGX Orin developer kit. Photo: Auledas, CC BY 4.0, via Wikimedia Commons.

AlteraFPGA (PCIe/dev kit)No licensed photo yet

Showing the newest results per platform and source. 12 superseded older results are hidden.Showing all results, including 12 superseded by newer results from the same source.

No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.

	NVIDIA Jetson AGX Orin 64GB	Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
Best object detection	435 FPS B 2026-10-13 (page last edited)	117 FPS D 2026-08-10 (published)
Power	65.00 W spec	n/a
Perf / W	6.69 FPS/W spec	n/a
Price	$3499 list	n/a
Workloads with data	3 of 7	3 of 7

Best published object detection result per platform. n/a = not published; never estimated.

Show data — all workloads, sources and like-for-like groups

object detection

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

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	435 FPS inference_time · b=1	YOLO26n INT8 · Ultralytics TensorRT · nano (YOLO-n)	B	65.00 W spec platform spec envelope (not measured with this result)	Ultralytics documentation (benchmark table) 2026-10-13 (page last edited)
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) MIXED: model-size class unknown vs nano (YOLO-n)	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)

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

instance segmentation

◌

No published instance segmentation results for NVIDIA Jetson AGX Orin 64GB 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.

pose estimation

◌

No published pose estimation results for NVIDIA Jetson AGX Orin 64GB 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.

image classification

Only Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) has published image classification results.

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)

NVIDIA Jetson AGX Orin 64GB:

◌

No published image classification results for NVIDIA Jetson AGX Orin 64GB 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.

semantic segmentation

⚠ MIXED COMPARISON — not like-for-like. Baseline mid-size CNN at batch 1. Differs: model-size class unknown 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)
NVIDIA Jetson AGX Orin 64GB MIXED: model-size class unknown vs mid-size CNN	104 FPS throughput · b=1	SegFormer-B0 (640x640) FP16 · TensorRT (ONNX export) · unknown	C	65.00 W spec platform spec envelope (not measured with this result)	arXiv 2608.00927 AgriJetsonBench (abstract figures) 2026-08-02 (published)

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

speech-to-text

◌

No published speech-to-text results for NVIDIA Jetson AGX Orin 64GB 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

Only NVIDIA Jetson AGX Orin 64GB has published LLM generation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	30.00 tok/s generation_throughput · b=1	Qwen 3 8B W4A16 · vLLM · LLM 5–14B	C	65.00 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson AI Lab benchmarks (benchmarks.json) 2026-07-21 (page last edited)

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

◌

No published LLM generation results for Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) or NVIDIA Jetson AGX Orin 64GB yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.

	NVIDIA Jetson AGX Orin 64GB	Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
Best object detection	435 FPS B 2026-10-13 (page last edited)	117 FPS D 2026-08-10 (published)
Power	65.00 W spec	n/a
Perf / W	6.69 FPS/W spec	n/a
Price	$3499 list	n/a
Workloads with data	5 of 7	3 of 7

Best published object detection result per platform. n/a = not published; never estimated.

Show data — all workloads, sources and like-for-like groups

object detection

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

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	435 FPS inference_time · b=1	YOLO26n INT8 · Ultralytics TensorRT · nano (YOLO-n)	B	65.00 W spec platform spec envelope (not measured with this result)	Ultralytics documentation (benchmark table) 2026-10-13 (page last edited)
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) MIXED: model-size class unknown vs nano (YOLO-n)	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)

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

instance segmentation

◌

pose estimation

◌

image classification

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

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)
NVIDIA Jetson AGX Orin 64GB MIXED: model-size class mid-size CNN vs mobile-class CNN; batch unknown vs 1	6424 FPS throughput_offline · b=unknown	MLPerf ResNet INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · mid-size CNN	D	65.00 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson Benchmarks (MLPerf v3.1 results 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: model-size class unknown 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)
NVIDIA Jetson AGX Orin 64GB MIXED: model-size class unknown vs mid-size CNN	104 FPS throughput · b=1	SegFormer-B0 (640x640) FP16 · TensorRT (ONNX export) · unknown	C	65.00 W spec platform spec envelope (not measured with this result)	arXiv 2608.00927 AgriJetsonBench (abstract figures) 2026-08-02 (published)

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

speech-to-text

Only NVIDIA Jetson AGX Orin 64GB has published speech-to-text results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	1170 FPS throughput_offline · b=unknown	MLPerf RNN-T INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · RNN-T	D	65.00 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson Benchmarks (MLPerf v3.1 results table) Older data (2023)

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

◌

No published speech-to-text results for Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) or NVIDIA Jetson AGX Orin 64GB 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 AGX Orin 64GB has published LLM generation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Orin 64GB	30.00 tok/s generation_throughput · b=1	Qwen 3 8B W4A16 · vLLM · LLM 5–14B	C	65.00 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson AI Lab benchmarks (benchmarks.json) 2026-07-21 (page last edited)

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

◌

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.