Danew Dslide_115
Geekbench AI Score
143
Single Precision Score
143
Half Precision Score
155
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 28 2025 12:48 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| 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% |
100
18.6 IPS |
|
|
Image Classification (HP)
|
100% |
92
17.1 IPS |
|
|
Image Classification (Q)
|
100% |
172
31.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
124
2.01 IPS |
|
|
Image Segmentation (HP)
|
100% |
123
1.99 IPS |
|
|
Image Segmentation (Q)
|
98% |
191
3.11 IPS |
|
|
Pose Estimation (SP)
|
100% |
351
0.41 IPS |
|
|
Pose Estimation (HP)
|
100% |
313
0.37 IPS |
|
|
Pose Estimation (Q)
|
84% |
224
0.27 IPS |
|
|
Object Detection (SP)
|
100% |
72
5.67 IPS |
|
|
Object Detection (HP)
|
100% |
68
5.43 IPS |
|
|
Object Detection (Q)
|
83% |
101
8.18 IPS |
|
|
Face Detection (SP)
|
100% |
170
2.02 IPS |
|
|
Face Detection (HP)
|
100% |
174
2.07 IPS |
|
|
Face Detection (Q)
|
95% |
236
2.82 IPS |
|
|
Depth Estimation (SP)
|
100% |
183
1.41 IPS |
|
|
Depth Estimation (HP)
|
99% |
204
1.57 IPS |
|
|
Depth Estimation (Q)
|
64% |
193
1.77 IPS |
|
|
Style Transfer (SP)
|
89% |
518
0.67 IPS |
|
|
Style Transfer (HP)
|
89% |
518
0.67 IPS |
|
|
Style Transfer (Q)
|
98% |
527
0.68 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
114
4.21 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
115
4.26 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
117
4.33 IPS |
|
|
Text Classification (SP)
|
100% |
63
83.8 IPS |
|
|
Text Classification (HP)
|
100% |
70
93.5 IPS |
|
|
Text Classification (Q)
|
88% |
85
114.6 IPS |
|
|
Machine Translation (SP)
|
100% |
105
1.80 IPS |
|
|
Machine Translation (HP)
|
100% |
106
1.82 IPS |
|
|
Machine Translation (Q)
|
50% |
48
1.69 IPS |
