Danew Dslide_115
Geekbench AI Score
144
Single Precision Score
141
Half Precision Score
158
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 02 2025 02:13 PM |
| Views | 6 |
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% |
93
17.3 IPS |
|
|
Image Classification (HP)
|
100% |
79
14.8 IPS |
|
|
Image Classification (Q)
|
100% |
101
18.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
84
1.37 IPS |
|
|
Image Segmentation (HP)
|
100% |
82
1.33 IPS |
|
|
Image Segmentation (Q)
|
98% |
144
2.34 IPS |
|
|
Pose Estimation (SP)
|
100% |
300
0.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
291
0.34 IPS |
|
|
Pose Estimation (Q)
|
84% |
227
0.27 IPS |
|
|
Object Detection (SP)
|
100% |
65
5.19 IPS |
|
|
Object Detection (HP)
|
100% |
69
5.49 IPS |
|
|
Object Detection (Q)
|
83% |
104
8.37 IPS |
|
|
Face Detection (SP)
|
100% |
181
2.16 IPS |
|
|
Face Detection (HP)
|
100% |
187
2.22 IPS |
|
|
Face Detection (Q)
|
95% |
262
3.13 IPS |
|
|
Depth Estimation (SP)
|
100% |
222
1.71 IPS |
|
|
Depth Estimation (HP)
|
99% |
193
1.49 IPS |
|
|
Depth Estimation (Q)
|
64% |
246
2.26 IPS |
|
|
Style Transfer (SP)
|
89% |
563
0.73 IPS |
|
|
Style Transfer (HP)
|
89% |
585
0.76 IPS |
|
|
Style Transfer (Q)
|
98% |
675
0.87 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
120
4.43 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
132
4.86 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
143
5.28 IPS |
|
|
Text Classification (SP)
|
100% |
82
109.8 IPS |
|
|
Text Classification (HP)
|
100% |
76
101.9 IPS |
|
|
Text Classification (Q)
|
88% |
93
125.9 IPS |
|
|
Machine Translation (SP)
|
100% |
118
2.04 IPS |
|
|
Machine Translation (HP)
|
100% |
118
2.04 IPS |
|
|
Machine Translation (Q)
|
50% |
50
1.78 IPS |
