HONOR ROD2-W09
Geekbench AI Score
1099
Single Precision Score
1039
Half Precision Score
1692
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | lsalthobaiti |
| Upload Date | November 06 2025 04:09 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR ROD2-W09 |
| Model ID | HONOR ROD2-W09 |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.01 GHz |
| Memory Information | |
|---|---|
| Size | 11.04 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1415
263.2 IPS |
|
|
Image Classification (HP)
|
100% |
606
112.7 IPS |
|
|
Image Classification (Q)
|
100% |
1120
208.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
565
9.17 IPS |
|
|
Image Segmentation (HP)
|
100% |
580
9.41 IPS |
|
|
Image Segmentation (Q)
|
98% |
1015
16.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
1653
1.93 IPS |
|
|
Pose Estimation (HP)
|
100% |
1642
1.92 IPS |
|
|
Pose Estimation (Q)
|
84% |
6345
7.52 IPS |
|
|
Object Detection (SP)
|
98% |
865
68.8 IPS |
|
|
Object Detection (HP)
|
98% |
568
45.2 IPS |
|
|
Object Detection (Q)
|
83% |
1077
87.0 IPS |
|
|
Face Detection (SP)
|
100% |
1223
14.5 IPS |
|
|
Face Detection (HP)
|
100% |
1104
13.1 IPS |
|
|
Face Detection (Q)
|
95% |
2736
32.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
1413
10.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
2357
18.2 IPS |
|
|
Depth Estimation (Q)
|
64% |
2613
23.9 IPS |
|
|
Style Transfer (SP)
|
89% |
7351
9.54 IPS |
|
|
Style Transfer (HP)
|
89% |
3153
4.09 IPS |
|
|
Style Transfer (Q)
|
98% |
5586
7.20 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
791
29.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
777
28.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3602
133.5 IPS |
|
|
Text Classification (SP)
|
100% |
315
420.8 IPS |
|
|
Text Classification (HP)
|
99% |
719
960.1 IPS |
|
|
Text Classification (Q)
|
88% |
540
727.8 IPS |
|
|
Machine Translation (SP)
|
100% |
713
12.3 IPS |
|
|
Machine Translation (HP)
|
100% |
980
16.9 IPS |
|
|
Machine Translation (Q)
|
50% |
320
11.4 IPS |
