SAMSUNG ELECTRONICS CO., LTD. 960XGL
Geekbench ML Score
3313
ONNX CPU Inference Score
Geekbench ML 0.6.0 for Windows AVX2
Result Information
| Upload Date | September 23 2024 03:03 PM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 960XGL |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP960XGL-XG1UK |
| Power Plan | SAMSUNG MODE |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 9 185H |
| Topology | 1 Processor, 16 Cores, 22 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 2.50 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 10 Cores |
| L1 Instruction Cache | 64.0 KB x 11 |
| L1 Data Cache | 48.0 KB x 11 |
| L2 Cache | 2.00 MB x 2 |
| L3 Cache | 24.0 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% |
1660
310.7 IPS |
|
|
Image Classification (F16)
|
100% |
1674
313.3 IPS |
|
|
Image Classification (I8)
|
99% |
2906
543.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
1480
24.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1512
25.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
2462
41.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
6530
7.91 IPS |
|
|
Pose Estimation (F16)
|
100% |
6521
7.90 IPS |
|
|
Pose Estimation (I8)
|
100% |
22334
27.0 IPS |
|
|
Object Detection (F32)
|
100% |
1684
125.7 IPS |
|
|
Object Detection (F16)
|
100% |
1667
124.5 IPS |
|
|
Object Detection (I8)
|
62% |
1489
111.2 IPS |
|
|
Face Detection (F32)
|
100% |
3661
43.5 IPS |
|
|
Face Detection (F16)
|
100% |
3653
43.4 IPS |
|
|
Face Detection (I8)
|
89% |
3853
45.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
7105
55.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
7035
54.6 IPS |
|
|
Depth Estimation (I8)
|
96% |
13266
102.9 IPS |
|
|
Style Transfer (F32)
|
100% |
15441
20.3 IPS |
|
|
Style Transfer (F16)
|
100% |
15541
20.4 IPS |
|
|
Style Transfer (I8)
|
98% |
20053
26.4 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2826
100.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2823
100.8 IPS |
|
|
Image Super-Resolution (I8)
|
99% |
4293
153.3 IPS |
|
|
Text Classification (F32)
|
100% |
1150
1.65 KIPS |
|
|
Text Classification (F16)
|
100% |
1149
1.65 KIPS |
|
|
Text Classification (I8)
|
98% |
408
586.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1659
30.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1696
31.2 IPS |
|
|
Machine Translation (I8)
|
67% |
2678
49.3 IPS |
