SAMSUNG ELECTRONICS CO., LTD. 960QHA
Geekbench AI Score
10204
Single Precision Score
26065
Half Precision Score
29352
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| Upload Date | November 11 2025 08:24 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | GPU |
| Device | Intel(R) Arc(TM) 140V GPU (16GB) (iGPU) |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | SAMSUNG ELECTRONICS CO., LTD. 960QHA |
| Motherboard | SAMSUNG ELECTRONICS CO., LTD. NT960QHA-K71AR |
| Power Plan | SAMSUNG MODE |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 7 258V |
| 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 | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
6970
1.30 KIPS |
|
|
Image Classification (HP)
|
100% |
14577
2.71 KIPS |
|
|
Image Classification (Q)
|
100% |
16288
3.03 KIPS |
|
|
Image Segmentation (SP)
|
100% |
8604
139.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
23737
384.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
27697
449.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
22102
25.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
122252
142.6 IPS |
|
|
Pose Estimation (Q)
|
97% |
248400
290.8 IPS |
|
|
Object Detection (SP)
|
100% |
5913
469.0 IPS |
|
|
Object Detection (HP)
|
100% |
14851
1.18 KIPS |
|
|
Object Detection (Q)
|
88% |
16579
1.33 KIPS |
|
|
Face Detection (SP)
|
100% |
13116
155.9 IPS |
|
|
Face Detection (HP)
|
100% |
32110
381.5 IPS |
|
|
Face Detection (Q)
|
100% |
41625
494.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
23039
177.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
58117
447.8 IPS |
|
|
Depth Estimation (Q)
|
89% |
68338
531.4 IPS |
|
|
Style Transfer (SP)
|
100% |
51493
66.2 IPS |
|
|
Style Transfer (HP)
|
100% |
145883
187.5 IPS |
|
|
Style Transfer (Q)
|
98% |
164866
212.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
9428
348.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
25811
953.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
28782
1.07 KIPS |
|
|
Text Classification (SP)
|
100% |
3443
4.59 KIPS |
|
|
Text Classification (HP)
|
100% |
5113
6.82 KIPS |
|
|
Text Classification (Q)
|
92% |
2945
3.96 KIPS |
|
|
Machine Translation (SP)
|
100% |
3093
53.3 IPS |
|
|
Machine Translation (HP)
|
98% |
6413
110.8 IPS |
|
|
Machine Translation (Q)
|
100% |
6428
110.7 IPS |
