Google rex
Geekbench AI Score
136
Single Precision Score
135
Half Precision Score
83
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | December 05 2024 05:58 AM |
| Views | 12 |
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% |
83
15.5 IPS |
|
|
Image Classification (HP)
|
100% |
83
15.5 IPS |
|
|
Image Classification (Q)
|
99% |
49
9.05 IPS |
|
|
Image Segmentation (SP)
|
100% |
104
1.69 IPS |
|
|
Image Segmentation (HP)
|
100% |
104
1.68 IPS |
|
|
Image Segmentation (Q)
|
98% |
51
0.83 IPS |
|
|
Pose Estimation (SP)
|
100% |
133
0.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
130
0.15 IPS |
|
|
Pose Estimation (Q)
|
98% |
138
0.16 IPS |
|
|
Object Detection (SP)
|
100% |
77
6.14 IPS |
|
|
Object Detection (HP)
|
100% |
77
6.09 IPS |
|
|
Object Detection (Q)
|
87% |
52
4.14 IPS |
|
|
Face Detection (SP)
|
100% |
248
2.95 IPS |
|
|
Face Detection (HP)
|
100% |
243
2.89 IPS |
|
|
Face Detection (Q)
|
97% |
91
1.08 IPS |
|
|
Depth Estimation (SP)
|
100% |
182
1.40 IPS |
|
|
Depth Estimation (HP)
|
99% |
187
1.44 IPS |
|
|
Depth Estimation (Q)
|
64% |
125
1.13 IPS |
|
|
Style Transfer (SP)
|
100% |
331
0.43 IPS |
|
|
Style Transfer (HP)
|
100% |
332
0.43 IPS |
|
|
Style Transfer (Q)
|
98% |
363
0.47 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
86
3.19 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
84
3.10 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
70
2.58 IPS |
|
|
Text Classification (SP)
|
100% |
102
135.5 IPS |
|
|
Text Classification (HP)
|
100% |
102
136.1 IPS |
|
|
Text Classification (Q)
|
91% |
50
67.7 IPS |
|
|
Machine Translation (SP)
|
100% |
200
3.44 IPS |
|
|
Machine Translation (HP)
|
100% |
189
3.26 IPS |
|
|
Machine Translation (Q)
|
57% |
64
1.56 IPS |
