Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) vs Raspberry Pi 5 + AI HAT+ (Hailo-8)

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Raspberry Pi AI HAT+ with Hailo-8 accelerator mounted on a Raspberry Pi, angled view — Raspberry Pi AI HAT+ (Hailo-8). Photo: SparkFun Electronics, CC BY 2.0, via Wikimedia Commons.

Showing the newest results per platform and source. 18 superseded older results are hidden.Showing all results, including 18 superseded by newer results from the same source.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)	Raspberry Pi 5 + AI HAT+ (Hailo-8)
Best semantic segmentation	5.24 FPS D Older data (2020)	28.74 FPS B 2026-10-11 (page last edited)
Power	n/a	n/a
Perf / W	n/a	n/a
Price	n/a	n/a
Workloads with data	1 of 7	3 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 Raspberry Pi 5 + AI HAT+ (Hailo-8) has published object detection results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Raspberry Pi 5 + AI HAT+ (Hailo-8)	46.08 FPS inference_time · b=1	YOLO26n INT8 · Ultralytics Hailo HEF / HailoRT · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics documentation: Hailo integration benchmark 2026-10-11 (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 Raspberry Pi 5 + AI HAT+ (Hailo-8) 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 Raspberry Pi 5 + AI HAT+ (Hailo-8) 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 Raspberry Pi 5 + AI HAT+ (Hailo-8) 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 Raspberry Pi 5 + AI HAT+ (Hailo-8) has published image classification results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Raspberry Pi 5 + AI HAT+ (Hailo-8)	500 FPS inference_time · b=1	YOLO26n-cls INT8 · Ultralytics Hailo HEF / HailoRT · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics documentation: Hailo integration benchmark 2026-10-11 (page last edited)

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

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No published image classification results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or Raspberry Pi 5 + AI HAT+ (Hailo-8) 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 nano (YOLO-n) at batch 1. Differs: model-size class mid-size CNN vs nano (YOLO-n).

Platform	Result	Model · precision · stack	Grade	Power	Source
Raspberry Pi 5 + AI HAT+ (Hailo-8)	28.74 FPS inference_time · b=1	YOLO26n-sem INT8 · Ultralytics Hailo HEF / HailoRT · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics documentation: Hailo integration benchmark 2026-10-11 (page last edited)
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) CPU-only MIXED: model-size class mid-size CNN vs nano (YOLO-n)	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)

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

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 Raspberry Pi 5 + AI HAT+ (Hailo-8) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

LLM generation

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No published LLM generation results for Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) or Raspberry Pi 5 + AI HAT+ (Hailo-8) 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)	Raspberry Pi 5 + AI HAT+ (Hailo-8)
Best object detection	3.55 FPS D Older data (2019)	76.99 FPS C 2025-12-16 (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	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 mobile-class CNN vs nano (YOLO-n).

Platform	Result	Model · precision · stack	Grade	Power	Source
Raspberry Pi 5 + AI HAT+ (Hailo-8)	46.08 FPS inference_time · b=1	YOLO26n INT8 · Ultralytics Hailo HEF / HailoRT · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics documentation: Hailo integration benchmark 2026-10-11 (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

⚠ 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
Raspberry Pi 5 + AI HAT+ (Hailo-8)	500 FPS inference_time · b=1	YOLO26n-cls INT8 · Ultralytics Hailo HEF / HailoRT · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics documentation: Hailo integration benchmark 2026-10-11 (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)	8.20 FPS inference_time · b=1	MobileNet v2 (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.

semantic segmentation

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

Platform	Result	Model · precision · stack	Grade	Power	Source
Raspberry Pi 5 + AI HAT+ (Hailo-8)	28.74 FPS inference_time · b=1	YOLO26n-sem INT8 · Ultralytics Hailo HEF / HailoRT · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics documentation: Hailo integration benchmark 2026-10-11 (page last edited)
Coral Dev Board CPU (quad Cortex-A53 @1.5 GHz, CPU only) CPU-only MIXED: model-size class mid-size CNN vs nano (YOLO-n)	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)

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

speech-to-text

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LLM generation

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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.