Danew Dslide_115
Geekbench AI Score
143
Single Precision Score
144
Half Precision Score
161
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 02 2025 01:45 PM |
| Views | 5 |
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% |
86
16.1 IPS |
|
|
Image Classification (HP)
|
100% |
88
16.3 IPS |
|
|
Image Classification (Q)
|
100% |
116
21.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
89
1.44 IPS |
|
|
Image Segmentation (HP)
|
100% |
88
1.43 IPS |
|
|
Image Segmentation (Q)
|
98% |
141
2.29 IPS |
|
|
Pose Estimation (SP)
|
100% |
300
0.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
305
0.36 IPS |
|
|
Pose Estimation (Q)
|
84% |
229
0.27 IPS |
|
|
Object Detection (SP)
|
100% |
71
5.65 IPS |
|
|
Object Detection (HP)
|
100% |
69
5.46 IPS |
|
|
Object Detection (Q)
|
83% |
113
9.10 IPS |
|
|
Face Detection (SP)
|
100% |
198
2.35 IPS |
|
|
Face Detection (HP)
|
100% |
192
2.28 IPS |
|
|
Face Detection (Q)
|
95% |
255
3.04 IPS |
|
|
Depth Estimation (SP)
|
100% |
183
1.41 IPS |
|
|
Depth Estimation (HP)
|
99% |
180
1.39 IPS |
|
|
Depth Estimation (Q)
|
64% |
238
2.18 IPS |
|
|
Style Transfer (SP)
|
89% |
582
0.76 IPS |
|
|
Style Transfer (HP)
|
89% |
591
0.77 IPS |
|
|
Style Transfer (Q)
|
98% |
692
0.89 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
128
4.72 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
126
4.64 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
152
5.63 IPS |
|
|
Text Classification (SP)
|
100% |
67
90.0 IPS |
|
|
Text Classification (HP)
|
100% |
80
106.1 IPS |
|
|
Text Classification (Q)
|
88% |
95
128.3 IPS |
|
|
Machine Translation (SP)
|
100% |
123
2.12 IPS |
|
|
Machine Translation (HP)
|
100% |
122
2.10 IPS |
|
|
Machine Translation (Q)
|
50% |
48
1.69 IPS |
