Dell Inc. OptiPlex 5080
Geekbench AI Score
1790
Single Precision Score
2580
Half Precision Score
2436
Quantized Score
Geekbench AI 1.6.0 Corporate for Windows AVX2
Result Information
| Upload Date | December 02 2025 08:33 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) UHD Graphics 630 (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Dell Inc. OptiPlex 5080 |
| Motherboard | Dell Inc. 00VTMF |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i7-10700 |
| Topology | 1 Processor, 8 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 5 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1078
200.6 IPS |
|
|
Image Classification (HP)
|
100% |
1737
323.1 IPS |
|
|
Image Classification (Q)
|
100% |
1590
295.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1543
25.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2390
38.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
2227
36.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2840
3.31 IPS |
|
|
Pose Estimation (HP)
|
99% |
2606
3.05 IPS |
|
|
Pose Estimation (Q)
|
97% |
3898
4.56 IPS |
|
|
Object Detection (SP)
|
100% |
1066
84.5 IPS |
|
|
Object Detection (HP)
|
99% |
1697
135.0 IPS |
|
|
Object Detection (Q)
|
88% |
1588
127.4 IPS |
|
|
Face Detection (SP)
|
100% |
3196
38.0 IPS |
|
|
Face Detection (HP)
|
100% |
5199
61.8 IPS |
|
|
Face Detection (Q)
|
97% |
4676
55.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
3286
25.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
5486
42.4 IPS |
|
|
Depth Estimation (Q)
|
89% |
5005
38.9 IPS |
|
|
Style Transfer (SP)
|
100% |
8049
10.3 IPS |
|
|
Style Transfer (HP)
|
100% |
10049
12.9 IPS |
|
|
Style Transfer (Q)
|
98% |
9224
11.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1367
50.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2374
87.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
2270
84.1 IPS |
|
|
Text Classification (SP)
|
71% |
621
897.8 IPS |
|
|
Text Classification (HP)
|
71% |
851
1.23 KIPS |
|
|
Text Classification (Q)
|
92% |
562
754.9 IPS |
|
|
Machine Translation (SP)
|
100% |
937
16.1 IPS |
|
|
Machine Translation (HP)
|
99% |
1233
21.3 IPS |
|
|
Machine Translation (Q)
|
98% |
1219
21.1 IPS |
