Danew Dslide_115
Geekbench AI Score
165
Single Precision Score
161
Half Precision Score
191
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 15 2025 04:22 PM |
| Views | 2 |
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% |
81
15.0 IPS |
|
|
Image Classification (HP)
|
100% |
88
16.4 IPS |
|
|
Image Classification (Q)
|
100% |
127
23.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
99
1.61 IPS |
|
|
Image Segmentation (HP)
|
100% |
103
1.67 IPS |
|
|
Image Segmentation (Q)
|
98% |
171
2.79 IPS |
|
|
Pose Estimation (SP)
|
100% |
334
0.39 IPS |
|
|
Pose Estimation (HP)
|
100% |
317
0.37 IPS |
|
|
Pose Estimation (Q)
|
84% |
290
0.34 IPS |
|
|
Object Detection (SP)
|
100% |
82
6.49 IPS |
|
|
Object Detection (HP)
|
100% |
79
6.29 IPS |
|
|
Object Detection (Q)
|
83% |
127
10.3 IPS |
|
|
Face Detection (SP)
|
100% |
200
2.37 IPS |
|
|
Face Detection (HP)
|
100% |
200
2.38 IPS |
|
|
Face Detection (Q)
|
95% |
291
3.48 IPS |
|
|
Depth Estimation (SP)
|
100% |
261
2.01 IPS |
|
|
Depth Estimation (HP)
|
99% |
203
1.57 IPS |
|
|
Depth Estimation (Q)
|
64% |
297
2.72 IPS |
|
|
Style Transfer (SP)
|
89% |
707
0.92 IPS |
|
|
Style Transfer (HP)
|
89% |
699
0.91 IPS |
|
|
Style Transfer (Q)
|
98% |
764
0.99 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
143
5.27 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
143
5.29 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
180
6.66 IPS |
|
|
Text Classification (SP)
|
100% |
96
128.2 IPS |
|
|
Text Classification (HP)
|
100% |
95
126.8 IPS |
|
|
Text Classification (Q)
|
88% |
113
151.9 IPS |
|
|
Machine Translation (SP)
|
100% |
140
2.41 IPS |
|
|
Machine Translation (HP)
|
100% |
139
2.39 IPS |
|
|
Machine Translation (Q)
|
50% |
61
2.17 IPS |
