Google rex
Geekbench AI Score
147
Single Precision Score
145
Half Precision Score
83
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 04 2024 08:23 AM |
| Views | 16 |
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% |
103
19.2 IPS |
|
|
Image Classification (HP)
|
100% |
101
18.8 IPS |
|
|
Image Classification (Q)
|
99% |
54
10.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
118
1.92 IPS |
|
|
Image Segmentation (HP)
|
100% |
120
1.95 IPS |
|
|
Image Segmentation (Q)
|
98% |
61
0.99 IPS |
|
|
Pose Estimation (SP)
|
100% |
155
0.18 IPS |
|
|
Pose Estimation (HP)
|
100% |
143
0.17 IPS |
|
|
Pose Estimation (Q)
|
98% |
124
0.15 IPS |
|
|
Object Detection (SP)
|
100% |
84
6.65 IPS |
|
|
Object Detection (HP)
|
100% |
85
6.76 IPS |
|
|
Object Detection (Q)
|
87% |
52
4.16 IPS |
|
|
Face Detection (SP)
|
100% |
259
3.07 IPS |
|
|
Face Detection (HP)
|
100% |
260
3.09 IPS |
|
|
Face Detection (Q)
|
97% |
97
1.16 IPS |
|
|
Depth Estimation (SP)
|
100% |
194
1.49 IPS |
|
|
Depth Estimation (HP)
|
99% |
195
1.50 IPS |
|
|
Depth Estimation (Q)
|
64% |
118
1.07 IPS |
|
|
Style Transfer (SP)
|
100% |
330
0.42 IPS |
|
|
Style Transfer (HP)
|
100% |
323
0.42 IPS |
|
|
Style Transfer (Q)
|
98% |
330
0.43 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
85
3.15 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
85
3.13 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
63
2.33 IPS |
|
|
Text Classification (SP)
|
100% |
117
156.1 IPS |
|
|
Text Classification (HP)
|
100% |
108
144.6 IPS |
|
|
Text Classification (Q)
|
91% |
53
70.6 IPS |
|
|
Machine Translation (SP)
|
100% |
191
3.30 IPS |
|
|
Machine Translation (HP)
|
100% |
191
3.30 IPS |
|
|
Machine Translation (Q)
|
57% |
60
1.48 IPS |
