Google rauru
Geekbench AI Score
659
Single Precision Score
662
Half Precision Score
1534
Quantized Score
Geekbench AI 1.4.0 for Android AArch64
Result Information
| Upload Date | August 26 2025 09:54 PM |
| Views | 2 |
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 | 14.14 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
402
74.8 IPS |
|
|
Image Classification (HP)
|
100% |
412
76.7 IPS |
|
|
Image Classification (Q)
|
99% |
1135
211.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
529
8.57 IPS |
|
|
Image Segmentation (HP)
|
100% |
536
8.69 IPS |
|
|
Image Segmentation (Q)
|
98% |
1094
17.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
684
0.80 IPS |
|
|
Pose Estimation (HP)
|
100% |
676
0.79 IPS |
|
|
Pose Estimation (Q)
|
98% |
2938
3.44 IPS |
|
|
Object Detection (SP)
|
100% |
400
31.7 IPS |
|
|
Object Detection (HP)
|
100% |
403
32.0 IPS |
|
|
Object Detection (Q)
|
87% |
1205
96.7 IPS |
|
|
Face Detection (SP)
|
100% |
935
11.1 IPS |
|
|
Face Detection (HP)
|
100% |
958
11.4 IPS |
|
|
Face Detection (Q)
|
97% |
2291
27.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
820
6.31 IPS |
|
|
Depth Estimation (HP)
|
99% |
825
6.36 IPS |
|
|
Depth Estimation (Q)
|
64% |
2042
18.5 IPS |
|
|
Style Transfer (SP)
|
100% |
1246
1.60 IPS |
|
|
Style Transfer (HP)
|
100% |
1244
1.60 IPS |
|
|
Style Transfer (Q)
|
98% |
3220
4.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
460
17.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
455
16.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1745
64.6 IPS |
|
|
Text Classification (SP)
|
100% |
655
873.9 IPS |
|
|
Text Classification (HP)
|
100% |
657
876.3 IPS |
|
|
Text Classification (Q)
|
91% |
939
1.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
930
16.0 IPS |
|
|
Machine Translation (HP)
|
100% |
926
15.9 IPS |
|
|
Machine Translation (Q)
|
57% |
665
16.2 IPS |
