WINCOR NIXDORF BEETLE /MIII
Geekbench AI Score
1455
Single Precision Score
745
Half Precision Score
2108
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | flintlock1 |
| Upload Date | April 08 2025 05:47 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i5-7500 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | WINCOR NIXDORF BEETLE /MIII |
| Motherboard | WINCOR NIXDORF M1.0-Q170-uATX |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i5-7500 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 9 |
| Base Frequency | 3.41 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1121
208.5 IPS |
|
|
Image Classification (HP)
|
100% |
289
53.8 IPS |
|
|
Image Classification (Q)
|
96% |
1814
338.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
568
9.21 IPS |
|
|
Image Segmentation (HP)
|
100% |
399
6.46 IPS |
|
|
Image Segmentation (Q)
|
97% |
1319
21.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
2385
2.78 IPS |
|
|
Pose Estimation (HP)
|
100% |
2105
2.46 IPS |
|
|
Pose Estimation (Q)
|
86% |
4517
5.34 IPS |
|
|
Object Detection (SP)
|
100% |
1040
82.5 IPS |
|
|
Object Detection (HP)
|
100% |
351
27.9 IPS |
|
|
Object Detection (Q)
|
58% |
1328
145.1 IPS |
|
|
Face Detection (SP)
|
100% |
1412
16.8 IPS |
|
|
Face Detection (HP)
|
100% |
661
7.86 IPS |
|
|
Face Detection (Q)
|
96% |
3272
39.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
2835
21.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
1062
8.18 IPS |
|
|
Depth Estimation (Q)
|
78% |
4095
32.7 IPS |
|
|
Style Transfer (SP)
|
100% |
5751
7.39 IPS |
|
|
Style Transfer (HP)
|
100% |
4824
6.20 IPS |
|
|
Style Transfer (Q)
|
87% |
6023
7.84 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1111
41.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
933
34.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1474
54.6 IPS |
|
|
Text Classification (SP)
|
100% |
1025
1.37 KIPS |
|
|
Text Classification (HP)
|
100% |
508
678.6 IPS |
|
|
Text Classification (Q)
|
97% |
882
1.18 KIPS |
|
|
Machine Translation (SP)
|
100% |
1033
17.8 IPS |
|
|
Machine Translation (HP)
|
100% |
387
6.67 IPS |
|
|
Machine Translation (Q)
|
68% |
1152
22.3 IPS |
