Dell Inc. OptiPlex 5080
Geekbench AI Score
2019
Single Precision Score
538
Half Precision Score
2957
Quantized Score
Geekbench AI 1.5.0-Beta1 Corporate for Linux AVX2
Result Information
| Upload Date | September 02 2025 05:00 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Intel Core i7-10700 |
| System Information | |
|---|---|
| Operating System | Ubuntu 22.04.4 LTS |
| Model | Dell Inc. OptiPlex 5080 |
| Motherboard | Dell Inc. 00VTMF |
| 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 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 15.33 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1059
197.0 IPS |
|
|
Image Classification (HP)
|
100% |
116
21.5 IPS |
|
|
Image Classification (Q)
|
94% |
2864
535.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1017
16.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
198
3.20 IPS |
|
|
Image Segmentation (Q)
|
98% |
1473
24.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
4532
5.29 IPS |
|
|
Pose Estimation (HP)
|
100% |
3134
3.66 IPS |
|
|
Pose Estimation (Q)
|
86% |
7395
8.74 IPS |
|
|
Object Detection (SP)
|
100% |
1253
99.4 IPS |
|
|
Object Detection (HP)
|
100% |
157
12.4 IPS |
|
|
Object Detection (Q)
|
58% |
1956
213.7 IPS |
|
|
Face Detection (SP)
|
100% |
1767
21.0 IPS |
|
|
Face Detection (HP)
|
100% |
256
3.05 IPS |
|
|
Face Detection (Q)
|
96% |
6349
75.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
4484
34.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
699
5.39 IPS |
|
|
Depth Estimation (Q)
|
78% |
6061
48.4 IPS |
|
|
Style Transfer (SP)
|
100% |
9935
12.8 IPS |
|
|
Style Transfer (HP)
|
100% |
8062
10.4 IPS |
|
|
Style Transfer (Q)
|
87% |
8749
11.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1634
60.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1219
45.0 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2028
75.1 IPS |
|
|
Text Classification (SP)
|
100% |
957
1.28 KIPS |
|
|
Text Classification (HP)
|
100% |
331
441.7 IPS |
|
|
Text Classification (Q)
|
97% |
773
1.04 KIPS |
|
|
Machine Translation (SP)
|
100% |
1501
25.9 IPS |
|
|
Machine Translation (HP)
|
100% |
312
5.38 IPS |
|
|
Machine Translation (Q)
|
68% |
1587
30.7 IPS |
