Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) vs NVIDIA Jetson Orin NX 16GB
No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.
| Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) | NVIDIA Jetson Orin NX 16GB | |
|---|---|---|
| Best semantic segmentation | 5.24 FPS D Older data (2020) | n/a |
| Power | n/a | n/a |
| Perf / W | n/a | n/a |
| Price | n/a | n/a |
| Workloads with data | 1 of 7 | 4 of 7 |
Best published semantic segmentation result per platform. n/a = not published; never estimated.
Show data — all workloads, sources and like-for-like groups
object detection
Only NVIDIA Jetson Orin NX 16GB has published object detection results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson Orin NX 16GB | 287 FPS inference_time · b=1 | YOLO26n INT8 · Ultralytics TensorRT · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics documentation (benchmark table) 2026-10-13 (page last edited) |
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):
No published object detection results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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.
instance segmentation
No published instance segmentation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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.
pose estimation
No published pose estimation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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.
image classification
Only NVIDIA Jetson Orin NX 16GB has published image classification results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson Orin NX 16GB | 2641 FPS throughput_offline · b=unknown | MLPerf ResNet INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · mid-size CNN | D | unknown power n/a no power published | NVIDIA Jetson Benchmarks (MLPerf v3.1 results table) Older data (2023) |
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):
No published image classification results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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.
semantic segmentation
Only Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) has published semantic segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) CPU-only | 5.24 FPS inference_time · b=1 | Unet Mv2 (128x128) TFLite on CPU · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN | D | unknown power n/a no power published | Google Coral Edge TPU benchmarks page (Table 1) Older data (2020) |
NVIDIA Jetson Orin NX 16GB:
No published semantic segmentation results for NVIDIA Jetson Orin NX 16GB or Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson Orin NX 16GB | 432 FPS throughput_offline · b=unknown | MLPerf RNN-T INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · RNN-T | D | unknown power n/a no power published | NVIDIA Jetson Benchmarks (MLPerf v3.1 results table) Older data (2023) |
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):
No published speech-to-text results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson Orin NX 16GB | 11.00 tok/s generation_throughput · b=1 | Nemotron Nano 9B V2 W4A16 · vLLM · LLM 5–14B | C | unknown power n/a no power published | NVIDIA Jetson AI Lab benchmarks (benchmarks.json) 2026-07-21 (page last edited) |
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):
No published LLM generation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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.
No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.
| Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) | NVIDIA Jetson Orin NX 16GB | |
|---|---|---|
| Best object detection | 3.55 FPS D Older data (2019) | 287 FPS B 2026-10-13 (page last edited) |
| Power | n/a | n/a |
| Perf / W | n/a | n/a |
| Price | n/a | n/a |
| Workloads with data | 3 of 7 | 4 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 Orin NX 16GB | 287 FPS inference_time · b=1 | YOLO26n INT8 · Ultralytics TensorRT · nano (YOLO-n) | B | unknown power n/a no power published | Ultralytics documentation (benchmark table) 2026-10-13 (page last edited) |
| Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) CPU-only MIXED: model-size class mobile-class CNN vs nano (YOLO-n) | 3.55 FPS inference_time · b=1 | MobileNet v2 SSD (224x224) TFLite on CPU · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mobile-class CNN | D | unknown power n/a no power published | Google Coral Edge TPU benchmarks page (Table 1) Older data (2019) |
No shared like-for-like group exists for this pair.
instance segmentation
No published instance segmentation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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.
pose estimation
No published pose estimation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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.
image classification
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) CPU-only | 0.570 FPS inference_time · b=1 | ResNet-50 V1 (299x299) TFLite on CPU · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN | D | unknown power n/a no power published | Google Coral Edge TPU benchmarks page (Table 1) Older data (2019) |
| NVIDIA Jetson Orin NX 16GB MIXED: batch unknown vs 1 | 2641 FPS throughput_offline · b=unknown | MLPerf ResNet INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · mid-size CNN | D | unknown 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 Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) has published semantic segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) CPU-only | 5.24 FPS inference_time · b=1 | Unet Mv2 (128x128) TFLite on CPU · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN | D | unknown power n/a no power published | Google Coral Edge TPU benchmarks page (Table 1) Older data (2020) |
NVIDIA Jetson Orin NX 16GB:
No published semantic segmentation results for NVIDIA Jetson Orin NX 16GB or Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson Orin NX 16GB | 432 FPS throughput_offline · b=unknown | MLPerf RNN-T INT8/FP16 (MLPerf closed) · TensorRT (MLPerf Inference, older round) · RNN-T | D | unknown power n/a no power published | NVIDIA Jetson Benchmarks (MLPerf v3.1 results table) Older data (2023) |
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):
No published speech-to-text results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson Orin NX 16GB | 11.00 tok/s generation_throughput · b=1 | Nemotron Nano 9B V2 W4A16 · vLLM · LLM 5–14B | C | unknown power n/a no power published | NVIDIA Jetson AI Lab benchmarks (benchmarks.json) 2026-07-21 (page last edited) |
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):
No published LLM generation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) 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
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.