SAMSUNG ELECTRONICS CO., LTD. 960QHA
Geekbench AI Score
3026
Single Precision Score
22585
Half Precision Score
34584
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| User | cfgauss1777 |
| Upload Date | May 09 2025 06:42 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 960QHA |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NP960QHA-KG2DE |
| 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 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1780
331.0 IPS |
|
|
Image Classification (HP)
|
100% |
12443
2.31 KIPS |
|
|
Image Classification (Q)
|
100% |
17925
3.33 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2280
37.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
16280
263.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
30249
490.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
3266
3.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
102470
119.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
198419
232.4 IPS |
|
|
Object Detection (SP)
|
100% |
1688
133.9 IPS |
|
|
Object Detection (HP)
|
100% |
15930
1.26 KIPS |
|
|
Object Detection (Q)
|
87% |
22919
1.84 KIPS |
|
|
Face Detection (SP)
|
100% |
4992
59.3 IPS |
|
|
Face Detection (HP)
|
100% |
28013
332.9 IPS |
|
|
Face Detection (Q)
|
100% |
68286
811.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
4438
34.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
69465
535.2 IPS |
|
|
Depth Estimation (Q)
|
88% |
111219
865.5 IPS |
|
|
Style Transfer (SP)
|
100% |
9745
12.5 IPS |
|
|
Style Transfer (HP)
|
100% |
185604
238.6 IPS |
|
|
Style Transfer (Q)
|
98% |
296732
382.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2036
75.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
32464
1.20 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57164
2.12 KIPS |
|
|
Text Classification (SP)
|
100% |
2042
2.73 KIPS |
|
|
Text Classification (HP)
|
100% |
2356
3.14 KIPS |
|
|
Text Classification (Q)
|
92% |
2101
2.82 KIPS |
|
|
Machine Translation (SP)
|
100% |
3211
55.3 IPS |
|
|
Machine Translation (HP)
|
100% |
3781
65.1 IPS |
|
|
Machine Translation (Q)
|
100% |
3668
63.2 IPS |
