SAMSUNG ELECTRONICS CO., LTD. 960XHA
Geekbench ML Score
3420
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | January 25 2025 06:18 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% |
1769
331.0 IPS |
|
|
Image Classification (F16)
|
100% |
1795
335.8 IPS |
|
|
Image Classification (I8)
|
99% |
3202
599.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1556
26.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1570
26.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
2606
43.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
4832
5.85 IPS |
|
|
Pose Estimation (F16)
|
100% |
4946
5.99 IPS |
|
|
Pose Estimation (I8)
|
100% |
17631
21.3 IPS |
|
|
Object Detection (F32)
|
100% |
1793
133.9 IPS |
|
|
Object Detection (F16)
|
100% |
1787
133.4 IPS |
|
|
Object Detection (I8)
|
62% |
1711
127.8 IPS |
|
|
Face Detection (F32)
|
100% |
3760
44.7 IPS |
|
|
Face Detection (F16)
|
100% |
3827
45.5 IPS |
|
|
Face Detection (I8)
|
89% |
4357
51.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
6192
48.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
6173
47.9 IPS |
|
|
Depth Estimation (I8)
|
96% |
13052
101.2 IPS |
|
|
Style Transfer (F32)
|
100% |
12392
16.3 IPS |
|
|
Style Transfer (F16)
|
100% |
12481
16.4 IPS |
|
|
Style Transfer (I8)
|
98% |
20876
27.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2705
96.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2611
93.3 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4609
164.6 IPS |
|
|
Text Classification (F32)
|
100% |
1317
1.89 KIPS |
|
|
Text Classification (F16)
|
100% |
1335
1.92 KIPS |
|
|
Text Classification (I8)
|
98% |
1170
1.68 KIPS |
|
|
Machine Translation (F32)
|
100% |
1973
36.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1932
35.6 IPS |
|
|
Machine Translation (I8)
|
67% |
2723
50.1 IPS |
