Micro-Star International Co., Ltd. Crosshair 17 C12VF
Geekbench ML Score
2378
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | April 26 2024 07:01 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1288
241.0 IPS |
|
|
Image Classification (F16)
|
100% |
1279
239.3 IPS |
|
|
Image Classification (I8)
|
99% |
2245
420.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1113
18.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1144
19.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
1500
25.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
3845
4.66 IPS |
|
|
Pose Estimation (F16)
|
100% |
4116
4.98 IPS |
|
|
Pose Estimation (I8)
|
100% |
12883
15.6 IPS |
|
|
Object Detection (F32)
|
100% |
1160
86.6 IPS |
|
|
Object Detection (F16)
|
100% |
1188
88.7 IPS |
|
|
Object Detection (I8)
|
62% |
1227
91.6 IPS |
|
|
Face Detection (F32)
|
100% |
2922
34.7 IPS |
|
|
Face Detection (F16)
|
100% |
2837
33.7 IPS |
|
|
Face Detection (I8)
|
89% |
3018
35.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
4407
34.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
4914
38.1 IPS |
|
|
Depth Estimation (I8)
|
96% |
8910
69.1 IPS |
|
|
Style Transfer (F32)
|
100% |
9000
11.8 IPS |
|
|
Style Transfer (F16)
|
100% |
9082
11.9 IPS |
|
|
Style Transfer (I8)
|
98% |
16381
21.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2149
76.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1988
71.0 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
2985
106.6 IPS |
|
|
Text Classification (F32)
|
100% |
1005
1.44 KIPS |
|
|
Text Classification (F16)
|
100% |
1022
1.47 KIPS |
|
|
Text Classification (I8)
|
98% |
335
481.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1322
24.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1248
23.0 IPS |
|
|
Machine Translation (I8)
|
67% |
1709
31.5 IPS |
