OBLUE OB-P10
Geekbench AI Score
1096
Single Precision Score
1073
Half Precision Score
2135
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 14 2025 01:19 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | OBLUE OB-P10 |
| Model ID | OBLUE OB-P10 |
| Motherboard | P10BoardV1 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 3.00 GHz |
| Cluster 3 | 1 Core @ 3.10 GHz |
| Memory Information | |
|---|---|
| Size | 15.15 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
617
114.7 IPS |
|
|
Image Classification (HP)
|
100% |
599
111.4 IPS |
|
|
Image Classification (Q)
|
100% |
1832
340.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
786
12.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
784
12.7 IPS |
|
|
Image Segmentation (Q)
|
98% |
1919
31.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2058
2.40 IPS |
|
|
Pose Estimation (HP)
|
100% |
2056
2.40 IPS |
|
|
Pose Estimation (Q)
|
84% |
3992
4.73 IPS |
|
|
Object Detection (SP)
|
100% |
466
37.0 IPS |
|
|
Object Detection (HP)
|
100% |
479
38.0 IPS |
|
|
Object Detection (Q)
|
83% |
1359
109.8 IPS |
|
|
Face Detection (SP)
|
100% |
1470
17.5 IPS |
|
|
Face Detection (HP)
|
100% |
1436
17.1 IPS |
|
|
Face Detection (Q)
|
95% |
3339
39.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
1935
14.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
1783
13.7 IPS |
|
|
Depth Estimation (Q)
|
64% |
3499
32.1 IPS |
|
|
Style Transfer (SP)
|
89% |
3863
5.01 IPS |
|
|
Style Transfer (HP)
|
89% |
3751
4.87 IPS |
|
|
Style Transfer (Q)
|
98% |
8682
11.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
950
35.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
957
35.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2183
80.9 IPS |
|
|
Text Classification (SP)
|
100% |
609
812.3 IPS |
|
|
Text Classification (HP)
|
100% |
629
840.0 IPS |
|
|
Text Classification (Q)
|
88% |
1125
1.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
852
14.7 IPS |
|
|
Machine Translation (HP)
|
100% |
763
13.1 IPS |
|
|
Machine Translation (Q)
|
50% |
416
14.8 IPS |
