Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) vs NVIDIA Jetson AGX Thor

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Showing the newest results per platform and source. 18 superseded older results are hidden.Showing all results, including 18 superseded by newer results from the same source.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.

	Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only)	NVIDIA Jetson AGX Thor
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	$5499 list
Workloads with data	1 of 7	2 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 AGX Thor has published object detection results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Thor	719 FPS inference_time · b=1	YOLO26n FP16 · Ultralytics TensorRT · nano (YOLO-n)	B	130 W spec platform spec envelope (not measured with this result)	Ultralytics documentation (benchmark table) 2026-10-13 (page last edited)

Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):

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No published object detection results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or NVIDIA Jetson AGX Thor yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

instance segmentation

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No published instance segmentation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or NVIDIA Jetson AGX Thor yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

pose estimation

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No published pose estimation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or NVIDIA Jetson AGX Thor yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

image classification

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No published image classification results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or NVIDIA Jetson AGX Thor 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 AGX Thor:

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No published semantic segmentation results for NVIDIA Jetson AGX Thor 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

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No published speech-to-text results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or NVIDIA Jetson AGX Thor 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 Thor has published LLM generation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Thor	41.32 tok/s tok/s gen, concurrency 1 · b=1	Deepseek R1 7B n/s on page · NVIDIA (vLLM/TensorRT-LLM per page) · LLM 5–14B	D	130 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson Benchmarks on or before 2025-11-08

Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):

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No published LLM generation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or NVIDIA Jetson AGX Thor 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 AGX Thor
Best object detection	3.55 FPS D Older data (2019)	719 FPS B 2026-10-13 (page last edited)
Power	n/a	130 W spec
Perf / W	n/a	5.53 FPS/W spec
Price	n/a	$5499 list
Workloads with data	3 of 7	2 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 mobile-class CNN vs nano (YOLO-n).

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Thor	719 FPS inference_time · b=1	YOLO26n FP16 · Ultralytics TensorRT · nano (YOLO-n)	B	130 W spec platform spec envelope (not measured with this result)	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

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pose estimation

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image classification

Only Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) has published image classification results.

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 AGX Thor:

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No published image classification results for NVIDIA Jetson AGX Thor 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.

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 AGX Thor:

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speech-to-text

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LLM generation

Only NVIDIA Jetson AGX Thor has published LLM generation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
NVIDIA Jetson AGX Thor	41.32 tok/s tok/s gen, concurrency 1 · b=1	Deepseek R1 7B n/s on page · NVIDIA (vLLM/TensorRT-LLM per page) · LLM 5–14B	D	130 W spec platform spec envelope (not measured with this result)	NVIDIA Jetson Benchmarks on or before 2025-11-08

Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only):

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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.