Danew Dslide_1095
Geekbench AI Score
222
Single Precision Score
211
Half Precision Score
447
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 14 2025 11:52 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Danew Dslide_1095 |
| Model ID | Danew Dslide_1095 |
| 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 | 2.72 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
105
19.5 IPS |
|
|
Image Classification (HP)
|
100% |
99
18.4 IPS |
|
|
Image Classification (Q)
|
100% |
317
58.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
120
1.94 IPS |
|
|
Image Segmentation (HP)
|
100% |
132
2.14 IPS |
|
|
Image Segmentation (Q)
|
98% |
417
6.77 IPS |
|
|
Pose Estimation (SP)
|
100% |
480
0.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
507
0.59 IPS |
|
|
Pose Estimation (Q)
|
84% |
1048
1.24 IPS |
|
|
Object Detection (SP)
|
100% |
117
9.28 IPS |
|
|
Object Detection (HP)
|
100% |
114
9.05 IPS |
|
|
Object Detection (Q)
|
83% |
307
24.8 IPS |
|
|
Face Detection (SP)
|
100% |
260
3.09 IPS |
|
|
Face Detection (HP)
|
100% |
260
3.09 IPS |
|
|
Face Detection (Q)
|
95% |
737
8.80 IPS |
|
|
Depth Estimation (SP)
|
100% |
345
2.66 IPS |
|
|
Depth Estimation (HP)
|
99% |
332
2.56 IPS |
|
|
Depth Estimation (Q)
|
64% |
943
8.64 IPS |
|
|
Style Transfer (SP)
|
89% |
1093
1.42 IPS |
|
|
Style Transfer (HP)
|
89% |
1111
1.44 IPS |
|
|
Style Transfer (Q)
|
98% |
2025
2.61 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
189
6.99 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
186
6.88 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
540
20.0 IPS |
|
|
Text Classification (SP)
|
100% |
130
173.5 IPS |
|
|
Text Classification (HP)
|
100% |
74
99.1 IPS |
|
|
Text Classification (Q)
|
88% |
138
185.7 IPS |
|
|
Machine Translation (SP)
|
100% |
176
3.02 IPS |
|
|
Machine Translation (HP)
|
100% |
177
3.05 IPS |
|
|
Machine Translation (Q)
|
50% |
72
2.55 IPS |
