AZW EQ
Geekbench AI Score
966
Single Precision Score
970
Half Precision Score
1847
Quantized Score
Geekbench AI 1.3.0 for Windows AVX2
Result Information
| Upload Date | June 16 2025 02:42 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | OpenVINO |
| Backend | CPU |
| Device | Intel(R) N150 |
| System Information | |
|---|---|
| Operating System | Microsoft Windows 11 Pro (64-bit) |
| Model | AZW EQ |
| Motherboard | AZW EQ |
| Power Plan | Balanced |
| CPU Information | |
|---|---|
| Name | Intel(R) N150 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 190 Stepping 0 |
| Base Frequency | 800 MHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
550
102.3 IPS |
|
|
Image Classification (HP)
|
100% |
548
102.0 IPS |
|
|
Image Classification (Q)
|
100% |
1123
208.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
634
10.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
636
10.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
1199
19.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
1074
1.25 IPS |
|
|
Pose Estimation (HP)
|
100% |
1073
1.25 IPS |
|
|
Pose Estimation (Q)
|
96% |
2512
2.94 IPS |
|
|
Object Detection (SP)
|
100% |
543
43.0 IPS |
|
|
Object Detection (HP)
|
100% |
553
43.8 IPS |
|
|
Object Detection (Q)
|
88% |
1138
91.2 IPS |
|
|
Face Detection (SP)
|
100% |
1514
18.0 IPS |
|
|
Face Detection (HP)
|
100% |
1531
18.2 IPS |
|
|
Face Detection (Q)
|
100% |
2880
34.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
1415
10.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
1425
11.0 IPS |
|
|
Depth Estimation (Q)
|
89% |
3055
23.8 IPS |
|
|
Style Transfer (SP)
|
100% |
3049
3.92 IPS |
|
|
Style Transfer (HP)
|
100% |
3059
3.93 IPS |
|
|
Style Transfer (Q)
|
98% |
7163
9.24 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
658
24.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
658
24.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
1473
54.6 IPS |
|
|
Text Classification (SP)
|
100% |
694
927.0 IPS |
|
|
Text Classification (HP)
|
100% |
695
927.3 IPS |
|
|
Text Classification (Q)
|
92% |
1104
1.48 KIPS |
|
|
Machine Translation (SP)
|
100% |
1167
20.1 IPS |
|
|
Machine Translation (HP)
|
100% |
1178
20.3 IPS |
|
|
Machine Translation (Q)
|
100% |
1173
20.2 IPS |
