Danew Dslide_114
Geekbench AI Score
148
Single Precision Score
148
Half Precision Score
257
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 19 2025 10:45 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Danew Dslide_114 |
| Model ID | Danew Dslide_114 |
| Motherboard | exdroid |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3333 revision 0 |
| Base Frequency | 1.42 GHz |
| Cluster 1 | 4 Cores @ 1.42 GHz |
| Cluster 2 | 4 Cores @ 1.80 GHz |
| Memory Information | |
|---|---|
| Size | 3.63 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
98
18.3 IPS |
|
|
Image Classification (HP)
|
100% |
102
18.9 IPS |
|
|
Image Classification (Q)
|
100% |
304
56.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
125
2.03 IPS |
|
|
Image Segmentation (HP)
|
100% |
129
2.09 IPS |
|
|
Image Segmentation (Q)
|
98% |
369
6.01 IPS |
|
|
Pose Estimation (SP)
|
100% |
449
0.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
434
0.51 IPS |
|
|
Pose Estimation (Q)
|
84% |
744
0.88 IPS |
|
|
Object Detection (SP)
|
100% |
103
8.19 IPS |
|
|
Object Detection (HP)
|
100% |
96
7.59 IPS |
|
|
Object Detection (Q)
|
83% |
257
20.7 IPS |
|
|
Face Detection (SP)
|
100% |
193
2.30 IPS |
|
|
Face Detection (HP)
|
100% |
157
1.87 IPS |
|
|
Face Detection (Q)
|
95% |
323
3.85 IPS |
|
|
Depth Estimation (SP)
|
100% |
218
1.68 IPS |
|
|
Depth Estimation (HP)
|
99% |
212
1.63 IPS |
|
|
Depth Estimation (Q)
|
64% |
347
3.18 IPS |
|
|
Style Transfer (SP)
|
89% |
500
0.65 IPS |
|
|
Style Transfer (HP)
|
89% |
505
0.66 IPS |
|
|
Style Transfer (Q)
|
98% |
958
1.24 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
105
3.88 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
111
4.11 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
190
7.04 IPS |
|
|
Text Classification (SP)
|
100% |
50
67.0 IPS |
|
|
Text Classification (HP)
|
100% |
59
78.8 IPS |
|
|
Text Classification (Q)
|
88% |
79
107.0 IPS |
|
|
Machine Translation (SP)
|
100% |
86
1.47 IPS |
|
|
Machine Translation (HP)
|
100% |
86
1.48 IPS |
|
|
Machine Translation (Q)
|
50% |
37
1.32 IPS |
