E.E.P.D. GmbH NUCE
Geekbench AI Score
1588
Single Precision Score
735
Half Precision Score
1976
Quantized Score
Geekbench AI 1.4.0 Corporate for Windows AVX2
Result Information
| Upload Date | July 01 2025 08:41 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% |
1458
271.1 IPS |
|
|
Image Classification (HP)
|
100% |
300
55.8 IPS |
|
|
Image Classification (Q)
|
96% |
1763
329.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
489
7.93 IPS |
|
|
Image Segmentation (HP)
|
100% |
360
5.83 IPS |
|
|
Image Segmentation (Q)
|
97% |
2342
38.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
3083
3.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
2549
2.97 IPS |
|
|
Pose Estimation (Q)
|
86% |
3793
4.48 IPS |
|
|
Object Detection (SP)
|
100% |
1433
113.7 IPS |
|
|
Object Detection (HP)
|
100% |
385
30.6 IPS |
|
|
Object Detection (Q)
|
58% |
1271
138.9 IPS |
|
|
Face Detection (SP)
|
100% |
2699
32.1 IPS |
|
|
Face Detection (HP)
|
100% |
754
8.96 IPS |
|
|
Face Detection (Q)
|
96% |
3078
36.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
3160
24.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
1028
7.92 IPS |
|
|
Depth Estimation (Q)
|
78% |
3293
26.3 IPS |
|
|
Style Transfer (SP)
|
100% |
6203
7.97 IPS |
|
|
Style Transfer (HP)
|
100% |
4897
6.29 IPS |
|
|
Style Transfer (Q)
|
87% |
6328
8.24 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1040
38.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
866
32.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1302
48.2 IPS |
|
|
Text Classification (SP)
|
100% |
643
858.6 IPS |
|
|
Text Classification (HP)
|
100% |
324
432.4 IPS |
|
|
Text Classification (Q)
|
97% |
514
688.8 IPS |
|
|
Machine Translation (SP)
|
100% |
918
15.8 IPS |
|
|
Machine Translation (HP)
|
100% |
410
7.07 IPS |
|
|
Machine Translation (Q)
|
68% |
1063
20.5 IPS |
