Google Coral Dev Board (Edge TPU) vs Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox)
Split result: Google Coral Dev Board (Edge TPU) is faster in 2 and Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) in 1 of 3 like-for-like comparisons.
| Google Coral Dev Board (Edge TPU) | Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) | |
|---|---|---|
| Best image classification | 500 FPS D undated | 672 FPS D undated |
| Power | 2.00 W spec | n/a |
| Perf / W | 250 FPS/W spec | n/a |
| Price | n/a | n/a |
| Workloads with data | 1 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
Only Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) has published object detection results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) | 25.81 FPS inference_time · b=1 | torchvision_ssdlite320_mobilenet_v3_large INT8 (VNNX) · VectorBlox SDK (VNNX), no compression · mobile-class CNN | D | unknown power n/a no power published | Microchip VectorBlox SDK tutorial metrics undated |
Google Coral Dev Board (Edge TPU):
No published object detection results for Google Coral Dev Board (Edge TPU) or Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
instance segmentation
Only Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) has published instance segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) | 14.13 FPS inference_time · b=1 | yolov8n-seg INT8 (VNNX) · VectorBlox SDK (VNNX), no compression · nano (YOLO-n) | D | unknown power n/a no power published | Microchip VectorBlox SDK tutorial metrics undated |
Google Coral Dev Board (Edge TPU):
No published instance segmentation results for Google Coral Dev Board (Edge TPU) or Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) 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 Google Coral Dev Board (Edge TPU) or Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) yet.
We only show cited public figures — nothing is estimated to fill gaps. Requests tell us what to source or test next.
image classification
| 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) undated |
| Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) | 68.35 FPS inference_time · b=1 | resnet18_86s_07p INT8 (VNNX) · VectorBlox SDK (VNNX), unstructured compression · mid-size CNN | D | unknown power n/a no power published | Microchip VectorBlox SDK tutorial metrics undated |
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) | 672 FPS inference_time · b=1 | mobilenet-v1-0.25-128 INT8 (VNNX) · VectorBlox SDK (VNNX), no compression · mobile-class CNN | D | unknown power n/a no power published | Microchip VectorBlox SDK tutorial metrics undated |
| 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) undated |
| 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) undated |
| Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) | 99.88 FPS inference_time · b=1 | onnx_squeezenet1.1 INT8 (VNNX) · VectorBlox SDK (VNNX), no compression · unknown | D | unknown power n/a no power published | Microchip VectorBlox SDK tutorial metrics undated |
semantic segmentation
No published semantic segmentation results for Google Coral Dev Board (Edge TPU) or Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) 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 Google Coral Dev Board (Edge TPU) or Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) 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 Google Coral Dev Board (Edge TPU) or Microchip PolarFire SoC Video Kit (VectorBlox CoreVectorBlox) 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
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.