Dell Inc. OptiPlex 9010
Geekbench ML Score
624
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows x86 (64-bit)
Result Information
| Upload Date | August 17 2024 10:25 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Dell Inc. OptiPlex 9010 |
| Motherboard | Dell Inc. 0M9KCM |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-3770 |
| Topology | 1 Processor, 4 Cores, 8 Threads |
| Identifier | GenuineIntel Family 6 Model 58 Stepping 9 |
| Base Frequency | 3.40 GHz |
| Cluster 1 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 4 |
| L1 Data Cache | 32.0 KB x 4 |
| L2 Cache | 256 KB x 4 |
| L3 Cache | 8.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
433
81.0 IPS |
|
|
Image Classification (F16)
|
100% |
413
77.2 IPS |
|
|
Image Classification (I8)
|
96% |
459
85.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
230
3.84 IPS |
|
|
Image Segmentation (F16)
|
100% |
284
4.74 IPS |
|
|
Image Segmentation (I8)
|
97% |
309
5.17 IPS |
|
|
Pose Estimation (F32)
|
100% |
697
0.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
614
0.74 IPS |
|
|
Pose Estimation (I8)
|
100% |
825
1.00 IPS |
|
|
Object Detection (F32)
|
100% |
266
19.9 IPS |
|
|
Object Detection (F16)
|
100% |
226
16.9 IPS |
|
|
Object Detection (I8)
|
62% |
308
23.0 IPS |
|
|
Face Detection (F32)
|
100% |
609
7.24 IPS |
|
|
Face Detection (F16)
|
100% |
583
6.93 IPS |
|
|
Face Detection (I8)
|
87% |
939
11.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1481
11.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
1400
10.9 IPS |
|
|
Depth Estimation (I8)
|
74% |
1443
11.2 IPS |
|
|
Style Transfer (F32)
|
100% |
2585
3.40 IPS |
|
|
Style Transfer (F16)
|
100% |
2938
3.86 IPS |
|
|
Style Transfer (I8)
|
85% |
2645
3.48 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
664
23.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
692
24.7 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
669
23.9 IPS |
|
|
Text Classification (F32)
|
100% |
521
748.2 IPS |
|
|
Text Classification (F16)
|
100% |
547
786.1 IPS |
|
|
Text Classification (I8)
|
94% |
221
317.1 IPS |
|
|
Machine Translation (F32)
|
100% |
634
11.7 IPS |
|
|
Machine Translation (F16)
|
100% |
624
11.5 IPS |
|
|
Machine Translation (I8)
|
67% |
450
8.28 IPS |
