Danew Dslide_115
Geekbench AI Score
140
Single Precision Score
140
Half Precision Score
155
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 19 2025 05:49 AM |
| Views | 4 |
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% |
70
13.1 IPS |
|
|
Image Classification (HP)
|
100% |
72
13.3 IPS |
|
|
Image Classification (Q)
|
100% |
105
19.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
98
1.58 IPS |
|
|
Image Segmentation (HP)
|
100% |
99
1.60 IPS |
|
|
Image Segmentation (Q)
|
98% |
154
2.51 IPS |
|
|
Pose Estimation (SP)
|
100% |
348
0.41 IPS |
|
|
Pose Estimation (HP)
|
100% |
339
0.40 IPS |
|
|
Pose Estimation (Q)
|
84% |
249
0.29 IPS |
|
|
Object Detection (SP)
|
100% |
78
6.19 IPS |
|
|
Object Detection (HP)
|
100% |
78
6.16 IPS |
|
|
Object Detection (Q)
|
83% |
106
8.54 IPS |
|
|
Face Detection (SP)
|
100% |
175
2.08 IPS |
|
|
Face Detection (HP)
|
100% |
177
2.10 IPS |
|
|
Face Detection (Q)
|
95% |
284
3.39 IPS |
|
|
Depth Estimation (SP)
|
100% |
183
1.41 IPS |
|
|
Depth Estimation (HP)
|
99% |
183
1.41 IPS |
|
|
Depth Estimation (Q)
|
64% |
254
2.32 IPS |
|
|
Style Transfer (SP)
|
89% |
609
0.79 IPS |
|
|
Style Transfer (HP)
|
89% |
609
0.79 IPS |
|
|
Style Transfer (Q)
|
98% |
567
0.73 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
115
4.24 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
114
4.23 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
145
5.38 IPS |
|
|
Text Classification (SP)
|
100% |
74
98.8 IPS |
|
|
Text Classification (HP)
|
100% |
72
95.8 IPS |
|
|
Text Classification (Q)
|
88% |
73
98.2 IPS |
|
|
Machine Translation (SP)
|
100% |
96
1.66 IPS |
|
|
Machine Translation (HP)
|
100% |
97
1.66 IPS |
|
|
Machine Translation (Q)
|
50% |
44
1.58 IPS |
