SAMSUNG ELECTRONICS CO., LTD. 960QHA
Geekbench ML Score
3481
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | October 10 2024 08:59 PM |
| Views | 3 |
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% |
1639
306.8 IPS |
|
|
Image Classification (F16)
|
100% |
1793
335.4 IPS |
|
|
Image Classification (I8)
|
99% |
2986
558.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1612
26.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
1608
26.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
2616
43.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
5110
6.19 IPS |
|
|
Pose Estimation (F16)
|
100% |
5081
6.15 IPS |
|
|
Pose Estimation (I8)
|
100% |
18189
22.0 IPS |
|
|
Object Detection (F32)
|
100% |
1751
130.7 IPS |
|
|
Object Detection (F16)
|
100% |
1828
136.4 IPS |
|
|
Object Detection (I8)
|
62% |
1791
133.7 IPS |
|
|
Face Detection (F32)
|
100% |
4063
48.3 IPS |
|
|
Face Detection (F16)
|
100% |
4078
48.5 IPS |
|
|
Face Detection (I8)
|
89% |
4487
53.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
6457
50.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
6451
50.0 IPS |
|
|
Depth Estimation (I8)
|
96% |
12962
100.5 IPS |
|
|
Style Transfer (F32)
|
100% |
12564
16.5 IPS |
|
|
Style Transfer (F16)
|
100% |
12630
16.6 IPS |
|
|
Style Transfer (I8)
|
98% |
21758
28.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2710
96.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2686
95.9 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4760
170.0 IPS |
|
|
Text Classification (F32)
|
100% |
1321
1.90 KIPS |
|
|
Text Classification (F16)
|
100% |
1324
1.90 KIPS |
|
|
Text Classification (I8)
|
98% |
1177
1.69 KIPS |
|
|
Machine Translation (F32)
|
100% |
2040
37.5 IPS |
|
|
Machine Translation (F16)
|
100% |
2016
37.1 IPS |
|
|
Machine Translation (I8)
|
67% |
2740
50.4 IPS |
