Danew Dslide_115
Geekbench AI Score
157
Single Precision Score
154
Half Precision Score
177
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | May 19 2025 01:06 PM |
| Views | 5 |
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% |
101
18.8 IPS |
|
|
Image Classification (HP)
|
100% |
81
15.1 IPS |
|
|
Image Classification (Q)
|
100% |
101
18.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
84
1.36 IPS |
|
|
Image Segmentation (HP)
|
100% |
83
1.34 IPS |
|
|
Image Segmentation (Q)
|
98% |
144
2.34 IPS |
|
|
Pose Estimation (SP)
|
100% |
294
0.34 IPS |
|
|
Pose Estimation (HP)
|
100% |
287
0.33 IPS |
|
|
Pose Estimation (Q)
|
84% |
250
0.30 IPS |
|
|
Object Detection (SP)
|
100% |
78
6.16 IPS |
|
|
Object Detection (HP)
|
100% |
83
6.56 IPS |
|
|
Object Detection (Q)
|
83% |
124
10.0 IPS |
|
|
Face Detection (SP)
|
100% |
203
2.42 IPS |
|
|
Face Detection (HP)
|
100% |
204
2.43 IPS |
|
|
Face Detection (Q)
|
95% |
306
3.66 IPS |
|
|
Depth Estimation (SP)
|
100% |
197
1.52 IPS |
|
|
Depth Estimation (HP)
|
99% |
193
1.49 IPS |
|
|
Depth Estimation (Q)
|
64% |
281
2.58 IPS |
|
|
Style Transfer (SP)
|
89% |
686
0.89 IPS |
|
|
Style Transfer (HP)
|
89% |
673
0.87 IPS |
|
|
Style Transfer (Q)
|
98% |
709
0.91 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
139
5.13 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
148
5.46 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
169
6.28 IPS |
|
|
Text Classification (SP)
|
100% |
91
121.5 IPS |
|
|
Text Classification (HP)
|
100% |
93
123.6 IPS |
|
|
Text Classification (Q)
|
88% |
108
145.1 IPS |
|
|
Machine Translation (SP)
|
100% |
135
2.32 IPS |
|
|
Machine Translation (HP)
|
100% |
137
2.35 IPS |
|
|
Machine Translation (Q)
|
50% |
61
2.15 IPS |
