SAMSUNG ELECTRONICS CO., LTD. 960QHA
Geekbench ML Score
3496
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | October 10 2024 09:00 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1811
338.9 IPS |
|
|
Image Classification (F16)
|
100% |
1800
336.7 IPS |
|
|
Image Classification (I8)
|
99% |
3311
619.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
1606
26.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1602
26.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
2653
44.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
5191
6.29 IPS |
|
|
Pose Estimation (F16)
|
100% |
4764
5.77 IPS |
|
|
Pose Estimation (I8)
|
100% |
18100
21.9 IPS |
|
|
Object Detection (F32)
|
100% |
1818
135.7 IPS |
|
|
Object Detection (F16)
|
100% |
1819
135.8 IPS |
|
|
Object Detection (I8)
|
62% |
1739
129.8 IPS |
|
|
Face Detection (F32)
|
100% |
4030
47.9 IPS |
|
|
Face Detection (F16)
|
100% |
4099
48.7 IPS |
|
|
Face Detection (I8)
|
89% |
4463
53.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
6326
49.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
6334
49.1 IPS |
|
|
Depth Estimation (I8)
|
96% |
12767
99.0 IPS |
|
|
Style Transfer (F32)
|
100% |
12733
16.7 IPS |
|
|
Style Transfer (F16)
|
100% |
12727
16.7 IPS |
|
|
Style Transfer (I8)
|
98% |
21568
28.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2696
96.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2756
98.4 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4770
170.4 IPS |
|
|
Text Classification (F32)
|
100% |
1341
1.93 KIPS |
|
|
Text Classification (F16)
|
100% |
1331
1.91 KIPS |
|
|
Text Classification (I8)
|
98% |
1163
1.67 KIPS |
|
|
Machine Translation (F32)
|
100% |
2000
36.8 IPS |
|
|
Machine Translation (F16)
|
100% |
2044
37.6 IPS |
|
|
Machine Translation (I8)
|
67% |
2716
50.0 IPS |
