Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) vs Google Coral Dev Board (Edge TPU)

AlteraFPGA (PCIe/dev kit)No licensed photo yet

Googleedge SBCNo licensed photo yet

Showing the newest results per platform and source. 18 superseded older results are hidden.Showing all results, including 18 superseded by newer results from the same source.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

	Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe)	Google Coral Dev Board (Edge TPU)
Best object detection	59.90 FPS D 2026-08-10 (published)	n/a
Power	n/a	n/a
Perf / W	n/a	n/a
Price	n/a	n/a
Workloads with data	2 of 7	1 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

Only Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) has published object detection results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe)	59.90 FPS throughput · b=1	yolo-v3-tiny-tf not stated in table (set by .arch file) · 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)

Google Coral Dev Board (Edge TPU):

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No published object detection results for Google Coral Dev Board (Edge TPU) or Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) 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 Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) or Google Coral Dev Board (Edge TPU) 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 Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) or Google Coral Dev Board (Edge TPU) 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 Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) has published image classification results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe)	160 FPS throughput · b=1	mobilenet-v2 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)

Google Coral Dev Board (Edge TPU):

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No published image classification results for Google Coral Dev Board (Edge TPU) or Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) 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 Google Coral Dev Board (Edge TPU) has published semantic segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Google Coral Dev Board (Edge TPU)	175 FPS inference_time · b=1	Unet Mv2 (128x128) INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN	D	2.00 W spec platform spec envelope (not measured with this result)	Google Coral Edge TPU benchmarks page (Table 1) Older data (2020)

Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe):

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No published semantic segmentation results for Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) or Google Coral Dev Board (Edge TPU) 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 Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) or Google Coral Dev Board (Edge TPU) 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 Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) or Google Coral Dev Board (Edge TPU) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.

Split result: Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) is faster in 1 and Google Coral Dev Board (Edge TPU) in 2 of 3 like-for-like comparisons.

	Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe)	Google Coral Dev Board (Edge TPU)
Best image classification	472 FPS D 2026-08-10 (published)	500 FPS D Older data (2019)
Power	n/a	2.00 W spec
Perf / W	n/a	250 FPS/W spec
Price	n/a	n/a
Workloads with data	2 of 7	3 of 7

Best published image classification result per platform (may be from different like-for-like groups — see data). 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 mobile-class CNN at batch 1. Differs: model-size class unknown vs mobile-class CNN.

Platform	Result	Model · precision · stack	Grade	Power	Source
Google Coral Dev Board (Edge TPU)	90.91 FPS inference_time · b=1	MobileNet v1 SSD (224x224) INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mobile-class CNN	D	2.00 W spec platform spec envelope (not measured with this result)	Google Coral Edge TPU benchmarks page (Table 1) Older data (2019)
Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe) MIXED: model-size class unknown vs mobile-class CNN	59.90 FPS throughput · b=1	yolo-v3-tiny-tf not stated in table (set by .arch file) · 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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pose estimation

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image classification

✓ Like-for-like: model-size class mid-size CNN, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe)	64.00 FPS throughput · b=1	resnet-50-tf 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)
Google Coral Dev Board (Edge TPU)	17.86 FPS inference_time · b=1	ResNet-50 V1 (299x299) INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN	D	2.00 W spec platform spec envelope (not measured with this result)	Google Coral Edge TPU benchmarks page (Table 1) Older data (2019)

✓ Like-for-like: model-size class mobile-class CNN, batch 1. Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
Google Coral Dev Board (Edge TPU)	417 FPS inference_time · b=1	MobileNet v1 (224x224) INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mobile-class CNN	D	2.00 W spec platform spec envelope (not measured with this result)	Google Coral Edge TPU benchmarks page (Table 1) Older data (2019)
Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe)	160 FPS throughput · b=1	mobilenet-v2 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)

✓ Like-for-like: model-size class unknown, batch 1 (size or batch not stated by source — unverified). Model, precision and stack may still differ.

Platform	Result	Model · precision · stack	Grade	Power	Source
Google Coral Dev Board (Edge TPU)	500 FPS inference_time · b=1	SqueezeNet (224x224) INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · unknown	D	2.00 W spec platform spec envelope (not measured with this result)	Google Coral Edge TPU benchmarks page (Table 1) Older data (2019)
Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe)	472 FPS throughput · b=1	squeezenet1.1 not stated in table (set by .arch file) · 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)

semantic segmentation

Only Google Coral Dev Board (Edge TPU) has published semantic segmentation results.

Platform	Result	Model · precision · stack	Grade	Power	Source
Google Coral Dev Board (Edge TPU)	175 FPS inference_time · b=1	Unet Mv2 (128x128) INT8 · TensorFlow Lite C++ benchmark (Edge TPU runtime) · mid-size CNN	D	2.00 W spec platform spec envelope (not measured with this result)	Google Coral Edge TPU benchmarks page (Table 1) Older data (2020)

Altera Agilex 5 FPGA E-Series 065B Modular Development Kit (FPGA AI Suite, OFS PCIe):

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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.