E.E.P.D. GmbH NUCE
Geekbench AI Score
1866
Single Precision Score
815
Half Precision Score
2301
Quantized Score
Geekbench AI 1.4.0 Corporate for Windows AVX2
Result Information
| Upload Date | July 01 2025 09:22 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | AMD Ryzen Embedded V2748 with Radeon Graphics |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 IoT LTSC (64-bit) |
| Model | E.E.P.D. GmbH NUCE |
| Motherboard | E.E.P.D. GmbH NUCE |
| CPU Information | |
|---|---|
| Name | AMD Ryzen Embedded V2748 with Radeon Graphics |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | AuthenticAMD Family 23 Model 96 Stepping 1 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1791
333.0 IPS |
|
|
Image Classification (HP)
|
100% |
322
59.9 IPS |
|
|
Image Classification (Q)
|
96% |
1910
356.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
507
8.21 IPS |
|
|
Image Segmentation (HP)
|
100% |
357
5.79 IPS |
|
|
Image Segmentation (Q)
|
97% |
2594
42.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
3917
4.57 IPS |
|
|
Pose Estimation (HP)
|
100% |
2628
3.07 IPS |
|
|
Pose Estimation (Q)
|
86% |
4050
4.79 IPS |
|
|
Object Detection (SP)
|
100% |
1566
124.2 IPS |
|
|
Object Detection (HP)
|
100% |
381
30.2 IPS |
|
|
Object Detection (Q)
|
58% |
1310
143.1 IPS |
|
|
Face Detection (SP)
|
100% |
2735
32.5 IPS |
|
|
Face Detection (HP)
|
100% |
797
9.47 IPS |
|
|
Face Detection (Q)
|
96% |
3825
45.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
4148
32.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
1188
9.15 IPS |
|
|
Depth Estimation (Q)
|
78% |
4401
35.1 IPS |
|
|
Style Transfer (SP)
|
100% |
7696
9.89 IPS |
|
|
Style Transfer (HP)
|
100% |
6071
7.80 IPS |
|
|
Style Transfer (Q)
|
87% |
7698
10.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1294
47.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1022
37.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1619
60.0 IPS |
|
|
Text Classification (SP)
|
100% |
777
1.04 KIPS |
|
|
Text Classification (HP)
|
100% |
407
543.0 IPS |
|
|
Text Classification (Q)
|
97% |
656
879.1 IPS |
|
|
Machine Translation (SP)
|
100% |
1052
18.1 IPS |
|
|
Machine Translation (HP)
|
100% |
472
8.12 IPS |
|
|
Machine Translation (Q)
|
68% |
1151
22.2 IPS |
