NVIDIA Jetson Orin Nano Super vs QuantaGrid D75H-10U (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.
| NVIDIA Jetson Orin Nano Super | QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) | |
|---|---|---|
| Best object detection | 263 FPS B 2026-10-13 (page last edited) | n/a |
| Power | 25.00 W spec | n/a |
| Perf / W | 10.53 FPS/W spec | n/a |
| Price | $249 list | 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 NVIDIA Jetson Orin Nano Super has published object detection results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson Orin Nano Super | 263 FPS inference_time · b=1 | YOLO26n INT8 · Ultralytics TensorRT · nano (YOLO-n) | B | 25.00 W spec reported in result source — spec | Ultralytics documentation (benchmark table) 2026-10-13 (page last edited) |
QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB):
No published object detection results for QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) or NVIDIA Jetson Orin Nano Super 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 NVIDIA Jetson Orin Nano Super or QuantaGrid D75H-10U (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 NVIDIA Jetson Orin Nano Super or QuantaGrid D75H-10U (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
No published image classification results for NVIDIA Jetson Orin Nano Super or QuantaGrid D75H-10U (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.
semantic segmentation
Only NVIDIA Jetson Orin Nano Super has published semantic segmentation results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| NVIDIA Jetson Orin Nano Super | 67.47 FPS throughput · b=1 | SegFormer-B0 (640x640) FP16 · TensorRT (ONNX export) · unknown | C | 25.00 W spec platform spec envelope (not measured with this result) | arXiv 2608.00927 AgriJetsonBench (abstract figures) 2026-08-02 (published) |
QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB):
No published semantic segmentation results for QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) or NVIDIA Jetson Orin Nano Super 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 QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) has published speech-to-text results.
| Platform | Result | Model · precision · stack | Grade | Power | Source |
|---|---|---|---|---|---|
| QuantaGrid D75H-10U (8x NVIDIA B300-SXM-270GB) | 45408 FPS throughput_offline · b=unknown | MLPerf whisper fp16 · TensorRT 10.14, CUDA 13.1, cuDNN 9.17, TensorRT-LLM feat/1.2-mlpinf, NVIDIA Dynamo mlperf-v6.0-dynamo-v0.8.0, vLLM CentM · unknown | A | unknown power n/a no power published | MLPerf Inference v6.1, closed division, data-centre suite 2026-09-16 (published) |
NVIDIA Jetson Orin Nano Super:
No published speech-to-text results for NVIDIA Jetson Orin Nano Super or QuantaGrid D75H-10U (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 NVIDIA Jetson Orin Nano Super or QuantaGrid D75H-10U (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.