Micro-Star International Co., Ltd. Sword 16 HX B14VGKG
Geekbench ML Score
3430
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | October 07 2024 09:55 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home Single Language (64-bit) |
| Model | Micro-Star International Co., Ltd. Sword 16 HX B14VGKG |
| Motherboard | Micro-Star International Co., Ltd. MS-15P2 |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core i7-14700HX |
| Topology | 1 Processor, 20 Cores, 28 Threads |
| Identifier | GenuineIntel Family 6 Model 183 Stepping 1 |
| Base Frequency | 2.10 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 12 Cores |
| L1 Instruction Cache | 32.0 KB x 14 |
| L1 Data Cache | 48.0 KB x 14 |
| L2 Cache | 2.00 MB x 3 |
| L3 Cache | 33.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1844
345.2 IPS |
|
|
Image Classification (F16)
|
100% |
1700
318.0 IPS |
|
|
Image Classification (I8)
|
99% |
3088
577.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1635
27.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1658
27.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
2313
38.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
7237
8.76 IPS |
|
|
Pose Estimation (F16)
|
100% |
7324
8.87 IPS |
|
|
Pose Estimation (I8)
|
100% |
19426
23.5 IPS |
|
|
Object Detection (F32)
|
100% |
1824
136.2 IPS |
|
|
Object Detection (F16)
|
100% |
1709
127.6 IPS |
|
|
Object Detection (I8)
|
62% |
1556
116.1 IPS |
|
|
Face Detection (F32)
|
100% |
3735
44.4 IPS |
|
|
Face Detection (F16)
|
100% |
3718
44.2 IPS |
|
|
Face Detection (I8)
|
89% |
3836
45.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
6928
53.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
7886
61.2 IPS |
|
|
Depth Estimation (I8)
|
96% |
12370
95.9 IPS |
|
|
Style Transfer (F32)
|
100% |
17220
22.7 IPS |
|
|
Style Transfer (F16)
|
100% |
17307
22.8 IPS |
|
|
Style Transfer (I8)
|
98% |
20959
27.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3147
112.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3188
113.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4500
160.7 IPS |
|
|
Text Classification (F32)
|
100% |
1248
1.79 KIPS |
|
|
Text Classification (F16)
|
100% |
1256
1.80 KIPS |
|
|
Text Classification (I8)
|
98% |
357
512.9 IPS |
|
|
Machine Translation (F32)
|
100% |
1706
31.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1683
31.0 IPS |
|
|
Machine Translation (I8)
|
67% |
2324
42.8 IPS |
