ADVAN 1406
Geekbench AI Score
2856
Single Precision Score
8850
Half Precision Score
13749
Quantized Score
Geekbench AI 1.5.0 for Windows AVX2
Result Information
| User | fadaf |
| Upload Date | December 18 2025 12:27 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | NPU |
| Device | Intel(R) AI Boost |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Home (64-bit) |
| Model | ADVAN 1406 |
| Motherboard | SU MTN39C-140M-PY |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel Core Ultra 5 125H |
| Topology | 1 Processor, 14 Cores, 18 Threads |
| Identifier | GenuineIntel Family 6 Model 170 Stepping 4 |
| Base Frequency | 3.60 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 10 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1366
254.1 IPS |
|
|
Image Classification (HP)
|
100% |
6224
1.16 KIPS |
|
|
Image Classification (Q)
|
100% |
8826
1.64 KIPS |
|
|
Image Segmentation (SP)
|
100% |
2305
37.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2439
39.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
2983
48.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
4552
5.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
29192
34.1 IPS |
|
|
Pose Estimation (Q)
|
96% |
63971
74.9 IPS |
|
|
Object Detection (SP)
|
100% |
1479
117.4 IPS |
|
|
Object Detection (HP)
|
100% |
5367
425.7 IPS |
|
|
Object Detection (Q)
|
88% |
9097
729.3 IPS |
|
|
Face Detection (SP)
|
100% |
4487
53.3 IPS |
|
|
Face Detection (HP)
|
100% |
15515
184.4 IPS |
|
|
Face Detection (Q)
|
100% |
28988
344.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
4514
34.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
16613
128.0 IPS |
|
|
Depth Estimation (Q)
|
88% |
30827
239.9 IPS |
|
|
Style Transfer (SP)
|
100% |
13465
17.3 IPS |
|
|
Style Transfer (HP)
|
100% |
47920
61.6 IPS |
|
|
Style Transfer (Q)
|
98% |
87639
113.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2243
82.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
14162
522.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
27154
1.01 KIPS |
|
|
Text Classification (SP)
|
100% |
1602
2.14 KIPS |
|
|
Text Classification (HP)
|
100% |
1772
2.37 KIPS |
|
|
Text Classification (Q)
|
92% |
1829
2.46 KIPS |
|
|
Machine Translation (SP)
|
100% |
1742
30.0 IPS |
|
|
Machine Translation (HP)
|
100% |
3999
68.9 IPS |
|
|
Machine Translation (Q)
|
100% |
4051
69.8 IPS |
