SAMSUNG ELECTRONICS CO., LTD. 960QHA
Geekbench ML Score
5260
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | October 10 2024 09:08 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 960QHA |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP960QHA-MSO |
| Power Plan | SAMSUNG MODE |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 258V |
| Topology | 1 Processor, 8 Cores |
| Identifier | GenuineIntel Family 6 Model 189 Stepping 1 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 64.0 KB x 4 |
| L1 Data Cache | 48.0 KB x 4 |
| L2 Cache | 2.50 MB x 1 |
| L3 Cache | 12.0 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | DirectML |
| Device | Intel(R) Arc(TM) 140V GPU (16GB) |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2605
487.5 IPS |
|
|
Image Classification (F16)
|
100% |
2800
524.0 IPS |
|
|
Image Classification (I8)
|
100% |
2228
417.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
6155
102.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
6053
101.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
4539
75.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
19612
23.7 IPS |
|
|
Pose Estimation (F16)
|
100% |
20122
24.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
16511
20.0 IPS |
|
|
Object Detection (F32)
|
100% |
2864
213.8 IPS |
|
|
Object Detection (F16)
|
100% |
2848
212.6 IPS |
|
|
Object Detection (I8)
|
61% |
2400
179.2 IPS |
|
|
Face Detection (F32)
|
100% |
7751
92.2 IPS |
|
|
Face Detection (F16)
|
100% |
7491
89.1 IPS |
|
|
Face Detection (I8)
|
89% |
5859
69.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
17649
136.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
17469
135.5 IPS |
|
|
Depth Estimation (I8)
|
94% |
14571
113.0 IPS |
|
|
Style Transfer (F32)
|
100% |
44485
58.5 IPS |
|
|
Style Transfer (F16)
|
100% |
47009
61.8 IPS |
|
|
Style Transfer (I8)
|
98% |
37102
48.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
7156
255.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7218
257.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
5047
180.2 IPS |
|
|
Text Classification (F32)
|
100% |
704
1.01 KIPS |
|
|
Text Classification (F16)
|
100% |
626
899.7 IPS |
|
|
Text Classification (I8)
|
98% |
464
667.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1490
27.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1524
28.0 IPS |
|
|
Machine Translation (I8)
|
70% |
848
15.6 IPS |
