SAMSUNG ELECTRONICS CO., LTD. 940XHA
Geekbench AI Score
3230
Single Precision Score
23132
Half Precision Score
35856
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | bourhene |
| Upload Date | June 23 2025 01:24 PM |
| Views | 9 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Famille (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 940XHA |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP940XHA-KG1FR |
| Power Plan | Utilisation normale |
| 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 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1941
360.9 IPS |
|
|
Image Classification (HP)
|
100% |
12484
2.32 KIPS |
|
|
Image Classification (Q)
|
100% |
19251
3.58 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2183
35.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
15289
247.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
29470
477.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
3468
4.05 IPS |
|
|
Pose Estimation (HP)
|
100% |
98701
115.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
190462
223.1 IPS |
|
|
Object Detection (SP)
|
100% |
1870
148.4 IPS |
|
|
Object Detection (HP)
|
100% |
16373
1.30 KIPS |
|
|
Object Detection (Q)
|
87% |
23357
1.87 KIPS |
|
|
Face Detection (SP)
|
100% |
5643
67.0 IPS |
|
|
Face Detection (HP)
|
100% |
28423
337.7 IPS |
|
|
Face Detection (Q)
|
100% |
61676
732.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
4796
36.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
68665
529.0 IPS |
|
|
Depth Estimation (Q)
|
88% |
111718
869.4 IPS |
|
|
Style Transfer (SP)
|
100% |
10126
13.0 IPS |
|
|
Style Transfer (HP)
|
100% |
195415
251.2 IPS |
|
|
Style Transfer (Q)
|
98% |
268621
346.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2166
80.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
32494
1.20 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
65197
2.41 KIPS |
|
|
Text Classification (SP)
|
100% |
2149
2.87 KIPS |
|
|
Text Classification (HP)
|
100% |
2950
3.94 KIPS |
|
|
Text Classification (Q)
|
92% |
2969
3.99 KIPS |
|
|
Machine Translation (SP)
|
100% |
3536
60.9 IPS |
|
|
Machine Translation (HP)
|
100% |
3891
67.0 IPS |
|
|
Machine Translation (Q)
|
100% |
3885
66.9 IPS |
