SAMSUNG ELECTRONICS CO., LTD. 960XHA
Geekbench ML Score
3403
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | January 25 2025 06:15 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 960XHA |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP960XHA-KG2US |
| Power Plan | SAMSUNG MODE |
| CPU Information | |
|---|---|
| Name | Intel(R) Core(TM) Ultra 7 256V |
| 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 | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | ONNX |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1786
334.2 IPS |
|
|
Image Classification (F16)
|
100% |
1751
327.7 IPS |
|
|
Image Classification (I8)
|
99% |
3260
610.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
1545
25.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
1561
26.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
2588
43.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
4862
5.89 IPS |
|
|
Pose Estimation (F16)
|
100% |
4875
5.90 IPS |
|
|
Pose Estimation (I8)
|
100% |
17349
21.0 IPS |
|
|
Object Detection (F32)
|
100% |
1791
133.7 IPS |
|
|
Object Detection (F16)
|
100% |
1789
133.6 IPS |
|
|
Object Detection (I8)
|
62% |
1693
126.4 IPS |
|
|
Face Detection (F32)
|
100% |
3621
43.1 IPS |
|
|
Face Detection (F16)
|
100% |
3807
45.3 IPS |
|
|
Face Detection (I8)
|
89% |
4290
51.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
5994
46.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
6162
47.8 IPS |
|
|
Depth Estimation (I8)
|
96% |
11610
90.0 IPS |
|
|
Style Transfer (F32)
|
100% |
11978
15.8 IPS |
|
|
Style Transfer (F16)
|
100% |
12183
16.0 IPS |
|
|
Style Transfer (I8)
|
98% |
20818
27.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2742
97.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2695
96.2 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4771
170.4 IPS |
|
|
Text Classification (F32)
|
100% |
1323
1.90 KIPS |
|
|
Text Classification (F16)
|
100% |
1329
1.91 KIPS |
|
|
Text Classification (I8)
|
98% |
1161
1.67 KIPS |
|
|
Machine Translation (F32)
|
100% |
2035
37.4 IPS |
|
|
Machine Translation (F16)
|
100% |
2030
37.4 IPS |
|
|
Machine Translation (I8)
|
67% |
2802
51.6 IPS |
