HONOR ROD2-W69
Geekbench AI Score
1274
Single Precision Score
1872
Half Precision Score
1476
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 01 2025 08:46 AM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM SM8635 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | HONOR ROD2-W69 |
| Model ID | HONOR ROD2-W69 |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM SM8635 |
| 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 | 14.95 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1015
188.7 IPS |
|
|
Image Classification (HP)
|
100% |
1487
276.6 IPS |
|
|
Image Classification (Q)
|
100% |
1125
209.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1660
26.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2663
43.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
1806
29.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
6818
7.96 IPS |
|
|
Pose Estimation (HP)
|
99% |
12001
14.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
11422
13.4 IPS |
|
|
Object Detection (SP)
|
100% |
708
56.1 IPS |
|
|
Object Detection (HP)
|
99% |
915
72.6 IPS |
|
|
Object Detection (Q)
|
87% |
843
67.7 IPS |
|
|
Face Detection (SP)
|
100% |
2477
29.4 IPS |
|
|
Face Detection (HP)
|
100% |
3898
46.3 IPS |
|
|
Face Detection (Q)
|
97% |
2860
34.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
3537
27.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
5280
40.8 IPS |
|
|
Depth Estimation (Q)
|
61% |
4053
39.9 IPS |
|
|
Style Transfer (SP)
|
100% |
8368
10.8 IPS |
|
|
Style Transfer (HP)
|
100% |
16136
20.7 IPS |
|
|
Style Transfer (Q)
|
98% |
15631
20.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1434
52.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2078
76.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2018
74.8 IPS |
|
|
Text Classification (SP)
|
35% |
30
294.9 IPS |
|
|
Text Classification (HP)
|
35% |
38
345.3 IPS |
|
|
Text Classification (Q)
|
33% |
29
342.8 IPS |
|
|
Machine Translation (SP)
|
100% |
440
7.58 IPS |
|
|
Machine Translation (HP)
|
97% |
465
8.05 IPS |
|
|
Machine Translation (Q)
|
43% |
238
13.5 IPS |
