Micro-Star International Co., Ltd. Crosshair 17 C12VF
Geekbench ML Score
10108
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | April 26 2024 07:05 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. Crosshair 17 C12VF |
| Motherboard | Micro-Star International Co., Ltd. MS-17L5 |
| Power Plan | Zrwnowaony |
| CPU Information | |
|---|---|
| Name | Intel Core i7-12650H |
| Topology | 1 Processor, 10 Cores, 16 Threads |
| Identifier | GenuineIntel Family 6 Model 154 Stepping 3 |
| Base Frequency | 2.30 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 32.0 KB x 8 |
| L1 Data Cache | 48.0 KB x 8 |
| L2 Cache | 1.25 MB x 2 |
| L3 Cache | 24.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4060 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
4152
777.0 IPS |
|
|
Image Classification (F16)
|
100% |
4373
818.3 IPS |
|
|
Image Classification (I8)
|
100% |
4036
755.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
8639
144.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
8600
143.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
7656
127.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
64390
78.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
63803
77.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
62185
75.3 IPS |
|
|
Object Detection (F32)
|
100% |
3667
273.7 IPS |
|
|
Object Detection (F16)
|
100% |
3213
239.9 IPS |
|
|
Object Detection (I8)
|
61% |
2881
215.1 IPS |
|
|
Face Detection (F32)
|
100% |
9357
111.3 IPS |
|
|
Face Detection (F16)
|
100% |
9605
114.2 IPS |
|
|
Face Detection (I8)
|
89% |
7704
91.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
28000
217.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
24228
187.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
25573
198.3 IPS |
|
|
Style Transfer (F32)
|
100% |
113128
148.8 IPS |
|
|
Style Transfer (F16)
|
100% |
115390
151.8 IPS |
|
|
Style Transfer (I8)
|
98% |
105770
139.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
22100
789.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
22423
800.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
16908
603.9 IPS |
|
|
Text Classification (F32)
|
100% |
2149
3.09 KIPS |
|
|
Text Classification (F16)
|
100% |
1959
2.81 KIPS |
|
|
Text Classification (I8)
|
98% |
1172
1.68 KIPS |
|
|
Machine Translation (F32)
|
100% |
1865
34.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1992
36.6 IPS |
|
|
Machine Translation (I8)
|
70% |
1500
27.6 IPS |
