Danew Dslide_115
Geekbench AI Score
143
Single Precision Score
142
Half Precision Score
148
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 02 2025 02:03 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 @ 1.51 GHz |
| Cluster 3 | 2 Cores @ 1.80 GHz |
| Memory Information | |
|---|---|
| Size | 3.66 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
67
12.5 IPS |
|
|
Image Classification (HP)
|
100% |
74
13.7 IPS |
|
|
Image Classification (Q)
|
100% |
92
17.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
95
1.53 IPS |
|
|
Image Segmentation (HP)
|
100% |
94
1.52 IPS |
|
|
Image Segmentation (Q)
|
98% |
132
2.15 IPS |
|
|
Pose Estimation (SP)
|
100% |
329
0.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
314
0.37 IPS |
|
|
Pose Estimation (Q)
|
84% |
239
0.28 IPS |
|
|
Object Detection (SP)
|
100% |
77
6.13 IPS |
|
|
Object Detection (HP)
|
100% |
77
6.11 IPS |
|
|
Object Detection (Q)
|
83% |
93
7.48 IPS |
|
|
Face Detection (SP)
|
100% |
181
2.16 IPS |
|
|
Face Detection (HP)
|
100% |
178
2.11 IPS |
|
|
Face Detection (Q)
|
95% |
246
2.94 IPS |
|
|
Depth Estimation (SP)
|
100% |
238
1.83 IPS |
|
|
Depth Estimation (HP)
|
99% |
239
1.84 IPS |
|
|
Depth Estimation (Q)
|
64% |
243
2.22 IPS |
|
|
Style Transfer (SP)
|
89% |
602
0.78 IPS |
|
|
Style Transfer (HP)
|
89% |
595
0.77 IPS |
|
|
Style Transfer (Q)
|
98% |
645
0.83 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
109
4.01 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
121
4.47 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
137
5.07 IPS |
|
|
Text Classification (SP)
|
100% |
69
92.1 IPS |
|
|
Text Classification (HP)
|
100% |
61
81.8 IPS |
|
|
Text Classification (Q)
|
88% |
75
100.9 IPS |
|
|
Machine Translation (SP)
|
100% |
116
2.00 IPS |
|
|
Machine Translation (HP)
|
100% |
113
1.94 IPS |
|
|
Machine Translation (Q)
|
50% |
50
1.76 IPS |
