Raspberry Pi 5 (CPU only) vs Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)

Raspberry Pi 5 single-board computer, top view, showing the Broadcom SoC, RAM, USB and Ethernet ports — Raspberry Pi 5. Photo: SimonWaldherr, CC BY 4.0, via Wikimedia Commons.

AlteraFPGA (PCIe/dev kit)No licensed photo yet

No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.

	Raspberry Pi 5 (CPU only)	Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite)
Best object detection	14.92 FPS B 2026-10-03 (page last edited)	117 FPS D 2026-08-10 (published)
Power	n/a	n/a
Perf / W	n/a	n/a
Price	n/a	n/a
Workloads with data	4 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 unknown vs nano (YOLO-n).

Platform	Result	Model · precision · stack	Grade	Power	Source
Raspberry Pi 5 (CPU only) CPU-only	14.92 FPS inference_time · b=1	YOLO26n FP32/default · Ultralytics NCNN · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics documentation (benchmark table) 2026-10-03 (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

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No published instance segmentation results for Raspberry Pi 5 (CPU only) 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

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No published pose estimation results for Raspberry Pi 5 (CPU only) 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 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 (CPU only) CPU-only	29.59 FPS inference_time · b=1	YOLO26n-cls FP32 · Ultralytics PyTorch (CPU) · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics documentation: Hailo integration benchmark 2026-10-11 (page last edited)
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) MIXED: model-size class mobile-class CNN vs nano (YOLO-n)	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)

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 (CPU only) CPU-only	1.20 FPS inference_time · b=1	YOLO26n-sem FP32 · Ultralytics PyTorch (CPU) · nano (YOLO-n)	B	unknown power n/a no power published	Ultralytics documentation: Hailo integration benchmark 2026-10-11 (page last edited)
Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) MIXED: model-size class mid-size CNN vs nano (YOLO-n)	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)

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

speech-to-text

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No published speech-to-text results for Raspberry Pi 5 (CPU only) 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 Raspberry Pi 5 (CPU only) has published LLM generation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Raspberry Pi 5 (CPU only) CPU-only	1.20 tok/s generation_throughput · b=1	DeepSeek R1 14b as in linked issue (Ollama default tags are 4-bit) · Ollama / llama.cpp (see linked issue) · LLM 5–14B	C	13.00 W measured reported in result source — measured	Jeff Geerling ai-benchmarks README (Findings tables) 2026-09-22 (page last edited)

Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite):

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No published LLM generation results for Terasic DE10-Agilex Development Board (Agilex 7, FPGA AI Suite) or Raspberry Pi 5 (CPU only) 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.