Danew Dslide_115
Geekbench AI Score
46
Single Precision Score
47
Half Precision Score
82
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 18 2025 06:31 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Danew Dslide_115 |
| Model ID | Danew Dslide_115 |
| Motherboard | exdroid |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.42 GHz |
| Cluster 1 | 4 Cores @ 1.42 GHz |
| Cluster 2 | 2 Cores @ 1.61 GHz |
| Cluster 3 | 2 Cores @ 1.80 GHz |
| Memory Information | |
|---|---|
| Size | 3.66 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
27
5.07 IPS |
|
|
Image Classification (HP)
|
100% |
28
5.12 IPS |
|
|
Image Classification (Q)
|
99% |
53
9.83 IPS |
|
|
Image Segmentation (SP)
|
100% |
37
0.60 IPS |
|
|
Image Segmentation (HP)
|
100% |
38
0.61 IPS |
|
|
Image Segmentation (Q)
|
98% |
60
0.98 IPS |
|
|
Pose Estimation (SP)
|
100% |
50
0.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
50
0.06 IPS |
|
|
Pose Estimation (Q)
|
98% |
116
0.14 IPS |
|
|
Object Detection (SP)
|
100% |
27
2.18 IPS |
|
|
Object Detection (HP)
|
100% |
27
2.18 IPS |
|
|
Object Detection (Q)
|
87% |
55
4.42 IPS |
|
|
Face Detection (SP)
|
100% |
71
0.84 IPS |
|
|
Face Detection (HP)
|
100% |
71
0.85 IPS |
|
|
Face Detection (Q)
|
97% |
125
1.49 IPS |
|
|
Depth Estimation (SP)
|
100% |
61
0.47 IPS |
|
|
Depth Estimation (HP)
|
99% |
61
0.47 IPS |
|
|
Depth Estimation (Q)
|
64% |
106
0.97 IPS |
|
|
Style Transfer (SP)
|
100% |
109
0.14 IPS |
|
|
Style Transfer (HP)
|
100% |
108
0.14 IPS |
|
|
Style Transfer (Q)
|
98% |
250
0.32 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
30
1.13 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31
1.13 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
67
2.48 IPS |
|
|
Text Classification (SP)
|
100% |
38
50.6 IPS |
|
|
Text Classification (HP)
|
100% |
38
51.1 IPS |
|
|
Text Classification (Q)
|
91% |
59
79.2 IPS |
|
|
Machine Translation (SP)
|
100% |
67
1.15 IPS |
|
|
Machine Translation (HP)
|
100% |
67
1.15 IPS |
|
|
Machine Translation (Q)
|
57% |
56
1.38 IPS |
