su-ONNX-UHD Dell Inc. Precision 5550
Geekbench AI Score
1003
Single Precision Score
1165
Half Precision Score
831
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | myi2000 |
| Upload Date | September 11 2025 04:34 AM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) UHD Graphics |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Dell Inc. Precision 5550 |
| Motherboard | Dell Inc. 0GX59H |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-10875H |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 2 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
407
75.8 IPS |
|
|
Image Classification (HP)
|
100% |
495
92.0 IPS |
|
|
Image Classification (Q)
|
100% |
422
78.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
646
10.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
728
11.8 IPS |
|
|
Image Segmentation (Q)
|
98% |
559
9.09 IPS |
|
|
Pose Estimation (SP)
|
100% |
2475
2.89 IPS |
|
|
Pose Estimation (HP)
|
100% |
3917
4.57 IPS |
|
|
Pose Estimation (Q)
|
97% |
2273
2.66 IPS |
|
|
Object Detection (SP)
|
100% |
512
40.6 IPS |
|
|
Object Detection (HP)
|
98% |
520
41.4 IPS |
|
|
Object Detection (Q)
|
86% |
469
37.7 IPS |
|
|
Face Detection (SP)
|
100% |
1037
12.3 IPS |
|
|
Face Detection (HP)
|
100% |
1183
14.1 IPS |
|
|
Face Detection (Q)
|
97% |
917
10.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
1855
14.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
2278
17.6 IPS |
|
|
Depth Estimation (Q)
|
77% |
1607
12.9 IPS |
|
|
Style Transfer (SP)
|
100% |
6214
7.99 IPS |
|
|
Style Transfer (HP)
|
100% |
9407
12.1 IPS |
|
|
Style Transfer (Q)
|
98% |
5551
7.16 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1238
45.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1733
64.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
978
36.2 IPS |
|
|
Text Classification (SP)
|
100% |
435
581.0 IPS |
|
|
Text Classification (HP)
|
100% |
293
391.6 IPS |
|
|
Text Classification (Q)
|
97% |
275
368.2 IPS |
|
|
Machine Translation (SP)
|
100% |
481
8.28 IPS |
|
|
Machine Translation (HP)
|
100% |
488
8.41 IPS |
|
|
Machine Translation (Q)
|
70% |
286
5.36 IPS |
