Micro-Star International Co., Ltd. MS-7D25
Geekbench ML Score
22663
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| User | metadex |
| Upload Date | October 16 2024 12:42 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | Micro-Star International Co., Ltd. MS-7D25 |
| Motherboard | Micro-Star International Co., Ltd. PRO Z690-A WIFI (MS-7D25) |
| Power Plan | Ultimate Performance |
| CPU Information | |
|---|---|
| Name | Intel Core i7-13700F |
| Topology | 1 Processor, 16 Cores, 24 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 8 Cores |
| L1 Instruction Cache | 32.0 KB x 12 |
| L1 Data Cache | 48.0 KB x 12 |
| L2 Cache | 2.00 MB x 3 |
| L3 Cache | 30.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4080 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
10355
1.94 KIPS |
|
|
Image Classification (F16)
|
100% |
10415
1.95 KIPS |
|
|
Image Classification (I8)
|
100% |
8670
1.62 KIPS |
|
|
Image Segmentation (F32)
|
100% |
15203
253.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
14378
240.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
14014
234.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
226505
274.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
230585
279.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
197143
238.7 IPS |
|
|
Object Detection (F32)
|
100% |
6823
509.4 IPS |
|
|
Object Detection (F16)
|
100% |
6639
495.7 IPS |
|
|
Object Detection (I8)
|
56% |
6403
478.0 IPS |
|
|
Face Detection (F32)
|
100% |
30338
360.7 IPS |
|
|
Face Detection (F16)
|
100% |
33428
397.5 IPS |
|
|
Face Detection (I8)
|
89% |
28241
335.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
64464
499.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
63063
489.1 IPS |
|
|
Depth Estimation (I8)
|
94% |
52393
406.3 IPS |
|
|
Style Transfer (F32)
|
100% |
316717
416.6 IPS |
|
|
Style Transfer (F16)
|
100% |
320163
421.1 IPS |
|
|
Style Transfer (I8)
|
98% |
255329
335.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
43995
1.57 KIPS |
|
|
Image Super-Resolution (F16)
|
100% |
43326
1.55 KIPS |
|
|
Image Super-Resolution (I8)
|
99% |
33751
1.21 KIPS |
|
|
Text Classification (F32)
|
100% |
2858
4.11 KIPS |
|
|
Text Classification (F16)
|
100% |
2966
4.26 KIPS |
|
|
Text Classification (I8)
|
98% |
1761
2.53 KIPS |
|
|
Machine Translation (F32)
|
100% |
3876
71.3 IPS |
|
|
Machine Translation (F16)
|
100% |
3930
72.3 IPS |
|
|
Machine Translation (I8)
|
70% |
2311
42.5 IPS |
