Micro-Star International Co., Ltd. Please change product name
Geekbench ML Score
2915
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | January 08 2024 05:59 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | Micro-Star International Co., Ltd. Please change product name |
| Motherboard | Micro-Star International Co., Ltd. MS-15A1 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 165H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 3.80 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 11 |
| L1 Data Cache | 48.0 KB x 11 |
| L2 Cache | 2.00 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% |
1522
284.8 IPS |
|
|
Image Classification (F16)
|
100% |
1534
287.1 IPS |
|
|
Image Classification (I8)
|
99% |
2778
519.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1400
23.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1322
22.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
2298
38.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
5570
6.75 IPS |
|
|
Pose Estimation (F16)
|
100% |
5557
6.73 IPS |
|
|
Pose Estimation (I8)
|
100% |
22354
27.1 IPS |
|
|
Object Detection (F32)
|
100% |
1574
117.5 IPS |
|
|
Object Detection (F16)
|
100% |
1552
115.8 IPS |
|
|
Object Detection (I8)
|
62% |
1456
108.7 IPS |
|
|
Face Detection (F32)
|
100% |
3461
41.1 IPS |
|
|
Face Detection (F16)
|
100% |
3413
40.6 IPS |
|
|
Face Detection (I8)
|
89% |
3594
42.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
6416
49.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
6434
49.9 IPS |
|
|
Depth Estimation (I8)
|
96% |
12007
93.1 IPS |
|
|
Style Transfer (F32)
|
100% |
13733
18.1 IPS |
|
|
Style Transfer (F16)
|
100% |
13774
18.1 IPS |
|
|
Style Transfer (I8)
|
98% |
17795
23.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2604
93.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2591
92.5 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
3952
141.1 IPS |
|
|
Text Classification (F32)
|
100% |
305
438.3 IPS |
|
|
Text Classification (F16)
|
100% |
1050
1.51 KIPS |
|
|
Text Classification (I8)
|
98% |
387
556.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1485
27.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1473
27.1 IPS |
|
|
Machine Translation (I8)
|
67% |
2502
46.1 IPS |
