MSI MS-7788
Geekbench ML Score
781
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows x86 (64-bit)
Result Information
| Upload Date | August 18 2024 09:52 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 10 Pro (64-bit) |
| Model | MSI MS-7788 |
| Motherboard | MSI H61M-P31/W8 (MS-7788) |
| Power Plan | High performance |
| CPU Information | |
|---|---|
| Name | Intel Core i5-3470 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 58 Stepping 9 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 2 |
| L1 Data Cache | 32.0 KB x 2 |
| L2 Cache | 256 KB x 2 |
| L3 Cache | 6.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
529
99.1 IPS |
|
|
Image Classification (F16)
|
100% |
464
86.9 IPS |
|
|
Image Classification (I8)
|
96% |
536
100.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
420
7.01 IPS |
|
|
Image Segmentation (F16)
|
100% |
411
6.87 IPS |
|
|
Image Segmentation (I8)
|
97% |
480
8.01 IPS |
|
|
Pose Estimation (F32)
|
100% |
1188
1.44 IPS |
|
|
Pose Estimation (F16)
|
100% |
1165
1.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1208
1.46 IPS |
|
|
Object Detection (F32)
|
100% |
503
37.5 IPS |
|
|
Object Detection (F16)
|
100% |
508
38.0 IPS |
|
|
Object Detection (I8)
|
62% |
454
33.9 IPS |
|
|
Face Detection (F32)
|
100% |
939
11.2 IPS |
|
|
Face Detection (F16)
|
100% |
938
11.2 IPS |
|
|
Face Detection (I8)
|
87% |
954
11.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1554
12.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
1578
12.2 IPS |
|
|
Depth Estimation (I8)
|
74% |
1290
10.0 IPS |
|
|
Style Transfer (F32)
|
100% |
2828
3.72 IPS |
|
|
Style Transfer (F16)
|
100% |
2909
3.83 IPS |
|
|
Style Transfer (I8)
|
85% |
2697
3.55 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
705
25.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
697
24.9 IPS |
|
|
Image Super-Resolution (I8)
|
97% |
656
23.4 IPS |
|
|
Text Classification (F32)
|
100% |
527
756.8 IPS |
|
|
Text Classification (F16)
|
100% |
542
779.6 IPS |
|
|
Text Classification (I8)
|
94% |
234
337.0 IPS |
|
|
Machine Translation (F32)
|
100% |
726
13.4 IPS |
|
|
Machine Translation (F16)
|
100% |
722
13.3 IPS |
|
|
Machine Translation (I8)
|
67% |
430
7.92 IPS |
