Google Coral Dev Board (Edge TPU) vs NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB)
No like-for-like comparison yet: both have published results, but model size or batch differ. Treat the numbers below as indicative only.
| Google Coral Dev Board (Edge TPU) | NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) | |
|---|---|---|
| Best image classification | 500 FPS D undated | n/a |
| 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 | 1 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
No published object detection results for Google Coral Dev Board (Edge TPU) or NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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 Google Coral Dev Board (Edge TPU) or NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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 NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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 Google Coral Dev Board (Edge TPU) has published image classification 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) undated |
NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB):
No published image classification results for NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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.
semantic segmentation
No published semantic segmentation results for Google Coral Dev Board (Edge TPU) or NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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
Only NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) has published speech-to-text results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) | 53267 FPS throughput_offline · b=unknown | MLPerf whisper fp16 · TensorRT 10.14, CUDA 13.1 · unknown | A | unknown power n/a no power published | MLPerf Inference v6.1 (closed, datacenter) ID B300-SXM-270GBx8_TRT undated |
Google Coral Dev Board (Edge TPU):
No published speech-to-text results for Google Coral Dev Board (Edge TPU) or NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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 NVIDIA DGX B300 (8x NVIDIA B300-SXM-270GB) 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.