motorola moto g05
Geekbench AI Score
82
Single Precision Score
116
Half Precision Score
114
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 03 2025 07:14 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | motorola moto g05 |
| Model ID | motorola moto g05 |
| Motherboard | lamu |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 3 part 3338 revision 1 |
| Base Frequency | 1.70 GHz |
| Cluster 1 | 6 Cores @ 1.70 GHz |
| Cluster 2 | 2 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 3.62 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
60
11.1 IPS |
|
|
Image Classification (HP)
|
100% |
95
17.6 IPS |
|
|
Image Classification (Q)
|
99% |
92
17.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
74
1.20 IPS |
|
|
Image Segmentation (HP)
|
100% |
131
2.12 IPS |
|
|
Image Segmentation (Q)
|
98% |
129
2.09 IPS |
|
|
Pose Estimation (SP)
|
100% |
48
0.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
67
0.08 IPS |
|
|
Pose Estimation (Q)
|
96% |
67
0.08 IPS |
|
|
Object Detection (SP)
|
100% |
46
3.68 IPS |
|
|
Object Detection (HP)
|
100% |
77
6.14 IPS |
|
|
Object Detection (Q)
|
83% |
75
6.07 IPS |
|
|
Face Detection (SP)
|
100% |
186
2.21 IPS |
|
|
Face Detection (HP)
|
100% |
274
3.26 IPS |
|
|
Face Detection (Q)
|
97% |
258
3.08 IPS |
|
|
Depth Estimation (SP)
|
100% |
102
0.78 IPS |
|
|
Depth Estimation (HP)
|
99% |
139
1.07 IPS |
|
|
Depth Estimation (Q)
|
62% |
111
1.05 IPS |
|
|
Style Transfer (SP)
|
100% |
195
0.25 IPS |
|
|
Style Transfer (HP)
|
100% |
308
0.40 IPS |
|
|
Style Transfer (Q)
|
98% |
306
0.39 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
56
2.07 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
85
3.13 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
84
3.12 IPS |
|
|
Text Classification (SP)
|
100% |
64
85.3 IPS |
|
|
Text Classification (HP)
|
100% |
64
84.8 IPS |
|
|
Text Classification (Q)
|
91% |
101
135.4 IPS |
|
|
Machine Translation (SP)
|
100% |
112
1.93 IPS |
|
|
Machine Translation (HP)
|
100% |
112
1.94 IPS |
|
|
Machine Translation (Q)
|
57% |
85
2.09 IPS |
