Google rex
Geekbench AI Score
116
Single Precision Score
117
Half Precision Score
83
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 05 2024 04:53 AM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | placeholder |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Google rex |
| Model ID | Google rex |
| Motherboard | karis |
| CPU Information | |
|---|---|
| Name | placeholder |
| Topology | 1 Processor, 14 Cores |
| Identifier | ARM implementer 78 architecture 8 variant 2 part 0 revision 1 |
| Base Frequency | 0 MHz |
| Cluster 1 | 14 Cores |
| Memory Information | |
|---|---|
| Size | 14.37 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
80
14.8 IPS |
|
|
Image Classification (HP)
|
100% |
77
14.3 IPS |
|
|
Image Classification (Q)
|
99% |
52
9.61 IPS |
|
|
Image Segmentation (SP)
|
100% |
84
1.36 IPS |
|
|
Image Segmentation (HP)
|
100% |
95
1.54 IPS |
|
|
Image Segmentation (Q)
|
98% |
58
0.94 IPS |
|
|
Pose Estimation (SP)
|
100% |
110
0.13 IPS |
|
|
Pose Estimation (HP)
|
100% |
109
0.13 IPS |
|
|
Pose Estimation (Q)
|
98% |
122
0.14 IPS |
|
|
Object Detection (SP)
|
100% |
65
5.15 IPS |
|
|
Object Detection (HP)
|
100% |
66
5.21 IPS |
|
|
Object Detection (Q)
|
87% |
52
4.19 IPS |
|
|
Face Detection (SP)
|
100% |
206
2.45 IPS |
|
|
Face Detection (HP)
|
100% |
209
2.48 IPS |
|
|
Face Detection (Q)
|
97% |
96
1.14 IPS |
|
|
Depth Estimation (SP)
|
100% |
157
1.21 IPS |
|
|
Depth Estimation (HP)
|
99% |
152
1.17 IPS |
|
|
Depth Estimation (Q)
|
64% |
117
1.06 IPS |
|
|
Style Transfer (SP)
|
100% |
269
0.35 IPS |
|
|
Style Transfer (HP)
|
100% |
270
0.35 IPS |
|
|
Style Transfer (Q)
|
98% |
322
0.42 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
70
2.59 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
70
2.57 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
65
2.40 IPS |
|
|
Text Classification (SP)
|
100% |
94
124.9 IPS |
|
|
Text Classification (HP)
|
100% |
99
132.2 IPS |
|
|
Text Classification (Q)
|
91% |
55
74.2 IPS |
|
|
Machine Translation (SP)
|
100% |
163
2.81 IPS |
|
|
Machine Translation (HP)
|
100% |
160
2.75 IPS |
|
|
Machine Translation (Q)
|
57% |
63
1.53 IPS |
