HWBench

NVIDIA Jetson Orin NX 16GB vs Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)

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.

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 Orin NX 16GBTerasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
Best object detection287 FPS B
2026-10-13 (page last edited)
117 FPS D
2026-08-10 (published)
Powern/an/a
Perf / Wn/an/a
Pricen/an/a
Workloads with data4 of 73 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).
PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson Orin NX 16GB287 FPS
inference_time · b=1
YOLO26n
INT8 · Ultralytics TensorRT · nano (YOLO-n)
Bunknown power n/a
no power published
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
Dunknown 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 Orin NX 16GB 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 Orin NX 16GB 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

⚠ 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.
PlatformResultModel · precision · stackGradePowerSource
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
Dunknown power n/a
no power published
Altera FPGA AI Suite Handbook (performance tables)
2026-08-10 (published)
NVIDIA Jetson Orin NX 16GB
MIXED: model-size class mid-size CNN vs mobile-class CNN; batch unknown vs 1
2641 FPS
throughput_offline · b=unknown
MLPerf ResNet
INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · mid-size CNN
Dunknown 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 Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) has published semantic segmentation results.

PlatformResultModel · precision · stackGradePowerSource
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
Dunknown power n/a
no power published
Altera FPGA AI Suite Handbook (performance tables)
2026-08-10 (published)

NVIDIA Jetson Orin NX 16GB:

◌

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

speech-to-text

Only NVIDIA Jetson Orin NX 16GB has published speech-to-text results.

PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson Orin NX 16GB432 FPS
throughput_offline · b=unknown
MLPerf RNN-T
INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · RNN-T
Dunknown power n/a
no power published
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 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.

PlatformResultModel · precision · stackGradePowerSource
NVIDIA Jetson Orin NX 16GB11.00 tok/s
generation_throughput · b=1
Nemotron Nano 9B V2
W4A16 · vLLM · LLM 5–14B
Cunknown power n/a
no power published
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 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.