Dell Inc. OptiPlex 7050
Geekbench AI Score
967
Single Precision Score
972
Half Precision Score
582
Quantized Score
Geekbench AI 1.1.0 for Linux AVX2
Result Information
| User | LaurentBonnaud |
| Upload Date | September 07 2024 09:20 AM |
| Views | 17 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Intel Core i5-6500 |
| System Information | |
|---|---|
| Operating System | Debian GNU/Linux trixie/sid |
| Model | Dell Inc. OptiPlex 7050 |
| Motherboard | Dell Inc. 0NW6H5 |
| CPU Information | |
|---|---|
| Name | Intel Core i5-6500 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 94 Stepping 3 |
| Base Frequency | 3.60 GHz |
| Cluster 1 | 0 Cores |
| Memory Information | |
|---|---|
| Size | 15.39 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
721
134.0 IPS |
|
|
Image Classification (HP)
|
100% |
731
136.0 IPS |
|
|
Image Classification (Q)
|
99% |
366
68.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
822
13.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
821
13.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
435
7.07 IPS |
|
|
Pose Estimation (SP)
|
100% |
1142
1.33 IPS |
|
|
Pose Estimation (HP)
|
100% |
1137
1.33 IPS |
|
|
Pose Estimation (Q)
|
96% |
1009
1.18 IPS |
|
|
Object Detection (SP)
|
100% |
729
57.8 IPS |
|
|
Object Detection (HP)
|
100% |
734
58.2 IPS |
|
|
Object Detection (Q)
|
85% |
402
32.4 IPS |
|
|
Face Detection (SP)
|
100% |
1132
13.5 IPS |
|
|
Face Detection (HP)
|
100% |
1133
13.5 IPS |
|
|
Face Detection (Q)
|
97% |
867
10.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
1137
8.76 IPS |
|
|
Depth Estimation (HP)
|
99% |
1139
8.77 IPS |
|
|
Depth Estimation (Q)
|
63% |
801
7.51 IPS |
|
|
Style Transfer (SP)
|
100% |
1487
1.91 IPS |
|
|
Style Transfer (HP)
|
100% |
1499
1.93 IPS |
|
|
Style Transfer (Q)
|
98% |
2118
2.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
645
23.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
646
23.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
575
21.3 IPS |
|
|
Text Classification (SP)
|
100% |
1024
1.37 KIPS |
|
|
Text Classification (HP)
|
100% |
1027
1.37 KIPS |
|
|
Text Classification (Q)
|
92% |
314
421.8 IPS |
|
|
Machine Translation (SP)
|
100% |
1158
20.0 IPS |
|
|
Machine Translation (HP)
|
100% |
1173
20.2 IPS |
|
|
Machine Translation (Q)
|
58% |
263
6.19 IPS |
