Micro-Star International Co., Ltd. WF75 10TJ
Geekbench ML Score
5015
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | February 23 2024 02:01 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 (64-bit) |
| Model | Micro-Star International Co., Ltd. WF75 10TJ |
| Motherboard | Micro-Star International Co., Ltd. MS-17F4 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-10750H |
| Topology | 1 Processor, 6 Cores, 12 Threads |
| Identifier | GenuineIntel Family 6 Model 165 Stepping 2 |
| Base Frequency | 2.59 GHz |
| Cluster 1 | 6 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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA Quadro T2000 |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2611
488.5 IPS |
|
|
Image Classification (F16)
|
100% |
2729
510.6 IPS |
|
|
Image Classification (I8)
|
100% |
2251
421.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
3189
53.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
3175
53.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
3013
50.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
24722
29.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
27589
33.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
24422
29.6 IPS |
|
|
Object Detection (F32)
|
100% |
1423
106.2 IPS |
|
|
Object Detection (F16)
|
100% |
1590
118.7 IPS |
|
|
Object Detection (I8)
|
60% |
1556
116.2 IPS |
|
|
Face Detection (F32)
|
100% |
5436
64.6 IPS |
|
|
Face Detection (F16)
|
100% |
5320
63.3 IPS |
|
|
Face Detection (I8)
|
89% |
4568
54.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
14287
110.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
14661
113.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
11799
91.5 IPS |
|
|
Style Transfer (F32)
|
100% |
49707
65.4 IPS |
|
|
Style Transfer (F16)
|
100% |
46075
60.6 IPS |
|
|
Style Transfer (I8)
|
98% |
39980
52.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
9962
355.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8971
320.4 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
6004
214.4 IPS |
|
|
Text Classification (F32)
|
100% |
1056
1.52 KIPS |
|
|
Text Classification (F16)
|
100% |
1083
1.56 KIPS |
|
|
Text Classification (I8)
|
98% |
651
936.1 IPS |
|
|
Machine Translation (F32)
|
100% |
1691
31.1 IPS |
|
|
Machine Translation (F16)
|
100% |
1725
31.7 IPS |
|
|
Machine Translation (I8)
|
70% |
1021
18.8 IPS |
