Danew Dslide_115
Geekbench AI Score
149
Single Precision Score
145
Half Precision Score
168
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 02 2025 12:03 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 @ 1.61 GHz |
| Cluster 3 | 2 Cores @ 1.80 GHz |
| Memory Information | |
|---|---|
| Size | 3.66 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
90
16.8 IPS |
|
|
Image Classification (HP)
|
100% |
85
15.8 IPS |
|
|
Image Classification (Q)
|
100% |
137
25.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
92
1.49 IPS |
|
|
Image Segmentation (HP)
|
100% |
98
1.59 IPS |
|
|
Image Segmentation (Q)
|
98% |
155
2.52 IPS |
|
|
Pose Estimation (SP)
|
100% |
304
0.35 IPS |
|
|
Pose Estimation (HP)
|
100% |
297
0.35 IPS |
|
|
Pose Estimation (Q)
|
84% |
231
0.27 IPS |
|
|
Object Detection (SP)
|
100% |
74
5.90 IPS |
|
|
Object Detection (HP)
|
100% |
72
5.74 IPS |
|
|
Object Detection (Q)
|
83% |
113
9.17 IPS |
|
|
Face Detection (SP)
|
100% |
191
2.28 IPS |
|
|
Face Detection (HP)
|
100% |
188
2.23 IPS |
|
|
Face Detection (Q)
|
95% |
271
3.23 IPS |
|
|
Depth Estimation (SP)
|
100% |
256
1.97 IPS |
|
|
Depth Estimation (HP)
|
99% |
186
1.43 IPS |
|
|
Depth Estimation (Q)
|
64% |
251
2.30 IPS |
|
|
Style Transfer (SP)
|
89% |
577
0.75 IPS |
|
|
Style Transfer (HP)
|
89% |
582
0.76 IPS |
|
|
Style Transfer (Q)
|
98% |
663
0.86 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
111
4.10 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
127
4.69 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
148
5.48 IPS |
|
|
Text Classification (SP)
|
100% |
77
102.6 IPS |
|
|
Text Classification (HP)
|
100% |
80
106.4 IPS |
|
|
Text Classification (Q)
|
88% |
96
129.9 IPS |
|
|
Machine Translation (SP)
|
100% |
121
2.08 IPS |
|
|
Machine Translation (HP)
|
100% |
118
2.04 IPS |
|
|
Machine Translation (Q)
|
50% |
51
1.81 IPS |
