Dell Inc. OptiPlex 5090
Geekbench ML Score
913
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Linux AVX2
Result Information
| Upload Date | August 16 2024 06:53 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Fedora Linux 40 (Cinnamon) |
| Model | Dell Inc. OptiPlex 5090 |
| Motherboard | Dell Inc. 0FXD80 |
| CPU Information | |
|---|---|
| Name | Intel Core i5-10505 |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 3 |
| Base Frequency | 4.60 GHz |
| Cluster 1 | 0 Cores |
| L1 Instruction Cache | 32.0 KB x 6 |
| L1 Data Cache | 32.0 KB x 6 |
| L2 Cache | 256 KB x 6 |
| L3 Cache | 12.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 15.35 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1068
199.9 IPS |
|
|
Image Classification (F16)
|
100% |
1041
194.7 IPS |
|
|
Image Classification (I8)
|
99% |
550
102.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
984
16.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
982
16.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
611
10.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1203
1.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
1109
1.34 IPS |
|
|
Pose Estimation (I8)
|
100% |
1164
1.41 IPS |
|
|
Object Detection (F32)
|
100% |
994
74.2 IPS |
|
|
Object Detection (F16)
|
100% |
680
50.8 IPS |
|
|
Object Detection (I8)
|
65% |
694
51.8 IPS |
|
|
Face Detection (F32)
|
100% |
1121
13.3 IPS |
|
|
Face Detection (F16)
|
100% |
1174
14.0 IPS |
|
|
Face Detection (I8)
|
87% |
1318
15.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1188
9.22 IPS |
|
|
Depth Estimation (F16)
|
100% |
1162
9.01 IPS |
|
|
Depth Estimation (I8)
|
95% |
1402
10.9 IPS |
|
|
Style Transfer (F32)
|
100% |
760
1.00 IPS |
|
|
Style Transfer (F16)
|
100% |
1178
1.55 IPS |
|
|
Style Transfer (I8)
|
98% |
2413
3.17 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
694
24.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
981
35.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
594
21.2 IPS |
|
|
Text Classification (F32)
|
100% |
832
1.20 KIPS |
|
|
Text Classification (F16)
|
100% |
784
1.13 KIPS |
|
|
Text Classification (I8)
|
92% |
334
480.5 IPS |
|
|
Machine Translation (F32)
|
100% |
892
16.4 IPS |
|
|
Machine Translation (F16)
|
100% |
972
17.9 IPS |
|
|
Machine Translation (I8)
|
62% |
462
8.50 IPS |
