HWBench

Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) vs Google Coral Dev Board (Edge TPU)

Showing the newest results per platform and source. 18 superseded older results are hidden.Showing all results, including 18 superseded by newer results from the same source.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 7 FPGA I-Series Development Kit (FPGA AI Suite)Google Coral Dev Board (Edge TPU)
Best image classification182 FPS D
2026-08-10 (published)
n/a
Powern/an/a
Perf / Wn/an/a
Pricen/an/a
Workloads with data1 of 71 of 7

Best published image classification result per platform. n/a = not published; never estimated.

Show data — all workloads, sources and like-for-like groups

object detection

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No published object detection results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) 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.

instance segmentation

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No published instance segmentation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) 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 7 FPGA I-Series Development Kit (FPGA AI Suite) 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 7 FPGA I-Series Development Kit (FPGA AI Suite) has published image classification results.

PlatformResultModel · precision · stackGradePowerSource
Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite)182 FPS
throughput · b=1
ResNet18 (PyTorch)
not stated in table · FPGA AI Suite on-chip parameter streaming; IP throughput · mid-size CNN
Dunknown power n/a
no power published
Altera FPGA AI Suite Handbook (performance tables)
2026-08-10 (published)

Google Coral Dev Board (Edge TPU):

◌

No published image classification results for Google Coral Dev Board (Edge TPU) or Altera Agilex 7 FPGA I-Series Development Kit (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.

semantic segmentation

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

PlatformResultModel · precision · stackGradePowerSource
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
D2.00 W spec
platform spec envelope (not measured with this result)
Google Coral Edge TPU benchmarks page (Table 1)
Older data (2020)

Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite):

◌

No published semantic segmentation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) 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 7 FPGA I-Series Development Kit (FPGA AI Suite) 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 7 FPGA I-Series Development Kit (FPGA AI Suite) 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.

Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) is faster in the only like-for-like comparison (largest gap: image classification, 10.19×).

Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite)Google Coral Dev Board (Edge TPU)
Best image classification182 FPS D
2026-08-10 (published)
500 FPS D
Older data (2019)
Powern/a2.00 W spec
Perf / Wn/a250 FPS/W spec
Pricen/an/a
Workloads with data1 of 73 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

Only Google Coral Dev Board (Edge TPU) has published object detection results.

PlatformResultModel · precision · stackGradePowerSource
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
D2.00 W spec
platform spec envelope (not measured with this result)
Google Coral Edge TPU benchmarks page (Table 1)
Older data (2019)

Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite):

◌

No published object detection results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) 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.

instance segmentation

◌

No published instance segmentation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) 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

◌

No published pose estimation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) 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

✓ Like-for-like: model-size class mid-size CNN, batch 1. Model, precision and stack may still differ.
PlatformResultModel · precision · stackGradePowerSource
Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite)182 FPS
throughput · b=1
ResNet18 (PyTorch)
not stated in table · FPGA AI Suite on-chip parameter streaming; IP throughput · mid-size CNN
Dunknown 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
D2.00 W spec
platform spec envelope (not measured with this result)
Google Coral Edge TPU benchmarks page (Table 1)
Older data (2019)

semantic segmentation

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

PlatformResultModel · precision · stackGradePowerSource
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
D2.00 W spec
platform spec envelope (not measured with this result)
Google Coral Edge TPU benchmarks page (Table 1)
Older data (2020)

Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite):

◌

No published semantic segmentation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) 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

◌

No published speech-to-text results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) 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

◌

No published LLM generation results for Altera Agilex 7 FPGA I-Series Development Kit (FPGA AI Suite) 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.

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.