NVIDIA Jetson AGX Orin 64GB vs Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
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
| 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
| 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
| 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
| 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
| 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):
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.
How to read these numbers
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.