Micro-Star International Co., Ltd. Sword 16 HX B14VGKG
Geekbench ML Score
12831
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | October 07 2024 09:56 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 | 64.0 KB x 14 |
| L1 Data Cache | 32.0 KB x 14 |
| L2 Cache | 4.00 MB x 3 |
| L3 Cache | 33.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | NVIDIA GeForce RTX 4070 Laptop GPU |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
7301
1.37 KIPS |
|
|
Image Classification (F16)
|
100% |
7410
1.39 KIPS |
|
|
Image Classification (I8)
|
100% |
6383
1.19 KIPS |
|
|
Image Segmentation (F32)
|
100% |
8488
141.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
8626
144.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
7885
131.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
75580
91.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
74239
89.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
70991
86.0 IPS |
|
|
Object Detection (F32)
|
100% |
4811
359.2 IPS |
|
|
Object Detection (F16)
|
100% |
5042
376.4 IPS |
|
|
Object Detection (I8)
|
63% |
4352
324.9 IPS |
|
|
Face Detection (F32)
|
100% |
15960
189.8 IPS |
|
|
Face Detection (F16)
|
100% |
18097
215.2 IPS |
|
|
Face Detection (I8)
|
89% |
15785
187.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
30102
233.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
38444
298.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
25046
194.2 IPS |
|
|
Style Transfer (F32)
|
100% |
146678
192.9 IPS |
|
|
Style Transfer (F16)
|
100% |
117583
154.7 IPS |
|
|
Style Transfer (I8)
|
98% |
108621
142.9 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
24314
868.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
25553
912.6 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
16567
591.7 IPS |
|
|
Text Classification (F32)
|
100% |
2196
3.16 KIPS |
|
|
Text Classification (F16)
|
100% |
2132
3.06 KIPS |
|
|
Text Classification (I8)
|
98% |
1090
1.57 KIPS |
|
|
Machine Translation (F32)
|
100% |
3194
58.8 IPS |
|
|
Machine Translation (F16)
|
100% |
3236
59.6 IPS |
|
|
Machine Translation (I8)
|
70% |
1573
28.9 IPS |
