Dell Inc. OptiPlex 3080
Geekbench AI Score
3818
Single Precision Score
3779
Half Precision Score
5933
Quantized Score
Geekbench AI 1.2.0 for Linux AVX2
Result Information
| User | jakesalleskovacs |
| Upload Date | March 06 2025 01:06 PM |
| Views | 14 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) i5-10600 CPU @ 3.30GHz |
| System Information | |
|---|---|
| Operating System | Debian GNU/Linux 12 (bookworm) |
| Model | Dell Inc. OptiPlex 3080 |
| Motherboard | Dell Inc. 0HMF7C |
| CPU Information | |
|---|---|
| Name | Intel Core i5-10600 |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 3 |
| Base Frequency | 4.80 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 62.55 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2374
441.5 IPS |
|
|
Image Classification (HP)
|
100% |
2362
439.2 IPS |
|
|
Image Classification (Q)
|
100% |
3760
699.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2469
40.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2484
40.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
4025
65.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
4941
5.77 IPS |
|
|
Pose Estimation (HP)
|
100% |
4921
5.74 IPS |
|
|
Pose Estimation (Q)
|
94% |
9521
11.2 IPS |
|
|
Object Detection (SP)
|
100% |
2326
184.5 IPS |
|
|
Object Detection (HP)
|
100% |
2168
172.0 IPS |
|
|
Object Detection (Q)
|
87% |
3935
315.6 IPS |
|
|
Face Detection (SP)
|
100% |
4163
49.5 IPS |
|
|
Face Detection (HP)
|
100% |
4170
49.5 IPS |
|
|
Face Detection (Q)
|
97% |
10007
119.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6329
48.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
6264
48.3 IPS |
|
|
Depth Estimation (Q)
|
81% |
10610
83.8 IPS |
|
|
Style Transfer (SP)
|
100% |
14013
18.0 IPS |
|
|
Style Transfer (HP)
|
100% |
14141
18.2 IPS |
|
|
Style Transfer (Q)
|
98% |
27121
35.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2933
108.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2927
108.1 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
5797
214.7 IPS |
|
|
Text Classification (SP)
|
100% |
2526
3.37 KIPS |
|
|
Text Classification (HP)
|
100% |
2528
3.37 KIPS |
|
|
Text Classification (Q)
|
91% |
1635
2.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
3576
61.6 IPS |
|
|
Machine Translation (HP)
|
100% |
3473
59.8 IPS |
|
|
Machine Translation (Q)
|
100% |
3496
60.2 IPS |
