Google rauru
Geekbench AI Score
322
Single Precision Score
471
Half Precision Score
1350
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 18 2025 03:30 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Google rauru |
| Model ID | Google rauru |
| Motherboard | navi |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3461 revision 1 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 4 Cores @ 2.40 GHz |
| Cluster 2 | 3 Cores @ 3.30 GHz |
| Cluster 3 | 1 Core @ 3.63 GHz |
| Memory Information | |
|---|---|
| Size | 10.28 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
116
21.7 IPS |
|
|
Image Classification (HP)
|
100% |
118
21.9 IPS |
|
|
Image Classification (Q)
|
99% |
1147
213.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
537
8.70 IPS |
|
|
Image Segmentation (HP)
|
100% |
540
8.75 IPS |
|
|
Image Segmentation (Q)
|
98% |
1083
17.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
199
0.23 IPS |
|
|
Pose Estimation (HP)
|
100% |
679
0.79 IPS |
|
|
Pose Estimation (Q)
|
98% |
2885
3.38 IPS |
|
|
Object Detection (SP)
|
100% |
392
31.1 IPS |
|
|
Object Detection (HP)
|
100% |
415
32.9 IPS |
|
|
Object Detection (Q)
|
87% |
1197
96.0 IPS |
|
|
Face Detection (SP)
|
100% |
312
3.71 IPS |
|
|
Face Detection (HP)
|
100% |
316
3.75 IPS |
|
|
Face Detection (Q)
|
97% |
626
7.46 IPS |
|
|
Depth Estimation (SP)
|
100% |
260
2.00 IPS |
|
|
Depth Estimation (HP)
|
99% |
261
2.01 IPS |
|
|
Depth Estimation (Q)
|
64% |
2144
19.5 IPS |
|
|
Style Transfer (SP)
|
100% |
423
0.54 IPS |
|
|
Style Transfer (HP)
|
100% |
1298
1.67 IPS |
|
|
Style Transfer (Q)
|
98% |
3302
4.26 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
455
16.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
456
16.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1710
63.4 IPS |
|
|
Text Classification (SP)
|
100% |
170
227.0 IPS |
|
|
Text Classification (HP)
|
100% |
666
889.1 IPS |
|
|
Text Classification (Q)
|
91% |
940
1.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
945
16.3 IPS |
|
|
Machine Translation (HP)
|
100% |
929
16.0 IPS |
|
|
Machine Translation (Q)
|
57% |
660
16.1 IPS |
