Danew Dslide_115
Geekbench AI Score
134
Single Precision Score
133
Half Precision Score
157
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 19 2025 03:40 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% |
82
15.3 IPS |
|
|
Image Classification (HP)
|
100% |
85
15.8 IPS |
|
|
Image Classification (Q)
|
100% |
137
25.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
115
1.86 IPS |
|
|
Image Segmentation (HP)
|
100% |
103
1.67 IPS |
|
|
Image Segmentation (Q)
|
98% |
185
3.01 IPS |
|
|
Pose Estimation (SP)
|
100% |
309
0.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
266
0.31 IPS |
|
|
Pose Estimation (Q)
|
84% |
190
0.23 IPS |
|
|
Object Detection (SP)
|
100% |
61
4.86 IPS |
|
|
Object Detection (HP)
|
100% |
63
5.01 IPS |
|
|
Object Detection (Q)
|
83% |
98
7.91 IPS |
|
|
Face Detection (SP)
|
100% |
172
2.04 IPS |
|
|
Face Detection (HP)
|
100% |
164
1.95 IPS |
|
|
Face Detection (Q)
|
95% |
292
3.48 IPS |
|
|
Depth Estimation (SP)
|
100% |
172
1.33 IPS |
|
|
Depth Estimation (HP)
|
99% |
180
1.39 IPS |
|
|
Depth Estimation (Q)
|
64% |
212
1.94 IPS |
|
|
Style Transfer (SP)
|
89% |
493
0.64 IPS |
|
|
Style Transfer (HP)
|
89% |
497
0.65 IPS |
|
|
Style Transfer (Q)
|
98% |
500
0.64 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
107
3.94 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
110
4.07 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
151
5.58 IPS |
|
|
Text Classification (SP)
|
100% |
77
102.2 IPS |
|
|
Text Classification (HP)
|
100% |
82
109.5 IPS |
|
|
Text Classification (Q)
|
88% |
95
127.7 IPS |
|
|
Machine Translation (SP)
|
100% |
92
1.59 IPS |
|
|
Machine Translation (HP)
|
100% |
91
1.57 IPS |
|
|
Machine Translation (Q)
|
50% |
45
1.60 IPS |
