Danew Dslide_1095
Geekbench AI Score
52
Single Precision Score
73
Half Precision Score
74
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 14 2025 01:29 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
35
6.44 IPS |
|
|
Image Classification (HP)
|
100% |
66
12.2 IPS |
|
|
Image Classification (Q)
|
99% |
64
11.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
44
0.71 IPS |
|
|
Image Segmentation (HP)
|
100% |
73
1.18 IPS |
|
|
Image Segmentation (Q)
|
98% |
70
1.14 IPS |
|
|
Pose Estimation (SP)
|
100% |
34
0.04 IPS |
|
|
Pose Estimation (HP)
|
100% |
40
0.05 IPS |
|
|
Pose Estimation (Q)
|
96% |
40
0.05 IPS |
|
|
Object Detection (SP)
|
100% |
29
2.29 IPS |
|
|
Object Detection (HP)
|
100% |
50
3.94 IPS |
|
|
Object Detection (Q)
|
83% |
49
3.95 IPS |
|
|
Face Detection (SP)
|
100% |
111
1.32 IPS |
|
|
Face Detection (HP)
|
100% |
167
1.98 IPS |
|
|
Face Detection (Q)
|
97% |
159
1.90 IPS |
|
|
Depth Estimation (SP)
|
100% |
63
0.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
83
0.64 IPS |
|
|
Depth Estimation (Q)
|
62% |
68
0.64 IPS |
|
|
Style Transfer (SP)
|
100% |
126
0.16 IPS |
|
|
Style Transfer (HP)
|
100% |
175
0.23 IPS |
|
|
Style Transfer (Q)
|
98% |
175
0.23 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
32
1.19 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50
1.85 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
50
1.84 IPS |
|
|
Text Classification (SP)
|
100% |
48
64.3 IPS |
|
|
Text Classification (HP)
|
100% |
49
64.8 IPS |
|
|
Text Classification (Q)
|
91% |
92
123.8 IPS |
|
|
Machine Translation (SP)
|
100% |
80
1.38 IPS |
|
|
Machine Translation (HP)
|
100% |
80
1.38 IPS |
|
|
Machine Translation (Q)
|
57% |
71
1.73 IPS |
