HONOR ROD2-W09
Geekbench AI Score
1290
Single Precision Score
1070
Half Precision Score
1707
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Annihilator |
| Upload Date | December 31 2024 08:24 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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% |
1070
199.0 IPS |
|
|
Image Classification (HP)
|
100% |
612
113.7 IPS |
|
|
Image Classification (Q)
|
100% |
1108
206.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1464
23.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1498
24.3 IPS |
|
|
Image Segmentation (Q)
|
98% |
1564
25.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2931
3.42 IPS |
|
|
Pose Estimation (HP)
|
100% |
2972
3.47 IPS |
|
|
Pose Estimation (Q)
|
84% |
2906
3.45 IPS |
|
|
Object Detection (SP)
|
98% |
598
47.6 IPS |
|
|
Object Detection (HP)
|
98% |
785
62.5 IPS |
|
|
Object Detection (Q)
|
83% |
1066
86.1 IPS |
|
|
Face Detection (SP)
|
100% |
1123
13.3 IPS |
|
|
Face Detection (HP)
|
100% |
1065
12.7 IPS |
|
|
Face Detection (Q)
|
95% |
2236
26.7 IPS |
|
|
Depth Estimation (SP)
|
99% |
2562
19.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
1368
10.6 IPS |
|
|
Depth Estimation (Q)
|
64% |
2387
21.9 IPS |
|
|
Style Transfer (SP)
|
89% |
7288
9.46 IPS |
|
|
Style Transfer (HP)
|
89% |
3268
4.24 IPS |
|
|
Style Transfer (Q)
|
98% |
13362
17.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
690
25.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
807
29.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1430
53.0 IPS |
|
|
Text Classification (SP)
|
100% |
327
436.3 IPS |
|
|
Text Classification (HP)
|
99% |
341
455.6 IPS |
|
|
Text Classification (Q)
|
88% |
547
737.2 IPS |
|
|
Machine Translation (SP)
|
100% |
983
16.9 IPS |
|
|
Machine Translation (HP)
|
100% |
708
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
704
25.0 IPS |
