SAMSUNG ELECTRONICS CO., LTD. 960XGL
Geekbench AI Score
3330
Single Precision Score
3335
Half Precision Score
7836
Quantized Score
Geekbench AI 1.2.0 for Windows AVX2
Result Information
| User | Angus72 |
| Upload Date | January 28 2025 10:08 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) Core(TM) Ultra 9 185H |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 960XGL |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP960XGL-XG1IT |
| 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 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1791
333.1 IPS |
|
|
Image Classification (HP)
|
100% |
1781
331.3 IPS |
|
|
Image Classification (Q)
|
100% |
4740
881.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2717
44.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2713
44.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
5302
86.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
4818
5.62 IPS |
|
|
Pose Estimation (HP)
|
100% |
4675
5.46 IPS |
|
|
Pose Estimation (Q)
|
96% |
16335
19.1 IPS |
|
|
Object Detection (SP)
|
100% |
1697
134.6 IPS |
|
|
Object Detection (HP)
|
100% |
1683
133.5 IPS |
|
|
Object Detection (Q)
|
88% |
4533
363.4 IPS |
|
|
Face Detection (SP)
|
100% |
5423
64.4 IPS |
|
|
Face Detection (HP)
|
100% |
5675
67.4 IPS |
|
|
Face Detection (Q)
|
100% |
11564
137.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
5569
42.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
5583
43.0 IPS |
|
|
Depth Estimation (Q)
|
89% |
13218
102.8 IPS |
|
|
Style Transfer (SP)
|
100% |
13633
17.5 IPS |
|
|
Style Transfer (HP)
|
100% |
13703
17.6 IPS |
|
|
Style Transfer (Q)
|
98% |
49034
63.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2463
90.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2531
93.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7786
288.3 IPS |
|
|
Text Classification (SP)
|
100% |
1937
2.58 KIPS |
|
|
Text Classification (HP)
|
100% |
1943
2.59 KIPS |
|
|
Text Classification (Q)
|
92% |
3718
4.99 KIPS |
|
|
Machine Translation (SP)
|
100% |
2147
37.0 IPS |
|
|
Machine Translation (HP)
|
100% |
2102
36.2 IPS |
|
|
Machine Translation (Q)
|
100% |
2164
37.3 IPS |
