SAMSUNG ELECTRONICS CO., LTD. 960QHA
Geekbench ML Score
5153
ONNX DirectML Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | October 10 2024 09:06 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% |
2623
490.9 IPS |
|
|
Image Classification (F16)
|
100% |
2551
477.4 IPS |
|
|
Image Classification (I8)
|
100% |
2207
412.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
6353
106.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
6228
104.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
4495
75.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
19837
24.0 IPS |
|
|
Pose Estimation (F16)
|
100% |
20056
24.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
16010
19.4 IPS |
|
|
Object Detection (F32)
|
100% |
2827
211.1 IPS |
|
|
Object Detection (F16)
|
100% |
2862
213.7 IPS |
|
|
Object Detection (I8)
|
61% |
2499
186.6 IPS |
|
|
Face Detection (F32)
|
100% |
7156
85.1 IPS |
|
|
Face Detection (F16)
|
100% |
7428
88.3 IPS |
|
|
Face Detection (I8)
|
89% |
4976
59.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
17934
139.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
17115
132.7 IPS |
|
|
Depth Estimation (I8)
|
94% |
13136
101.9 IPS |
|
|
Style Transfer (F32)
|
100% |
44483
58.5 IPS |
|
|
Style Transfer (F16)
|
100% |
44285
58.3 IPS |
|
|
Style Transfer (I8)
|
98% |
35083
46.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6816
243.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
7902
282.2 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
5023
179.4 IPS |
|
|
Text Classification (F32)
|
100% |
693
995.8 IPS |
|
|
Text Classification (F16)
|
100% |
604
868.5 IPS |
|
|
Text Classification (I8)
|
98% |
407
584.3 IPS |
|
|
Machine Translation (F32)
|
100% |
1549
28.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1485
27.3 IPS |
|
|
Machine Translation (I8)
|
70% |
871
16.0 IPS |
