vivo V2502A
Geekbench AI Score
607
Single Precision Score
609
Half Precision Score
1369
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 08 2025 02:13 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | vivo V2502A |
| Model ID | vivo V2502A |
| Motherboard | k6993v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3468 revision 0 |
| Base Frequency | 2.70 GHz |
| Cluster 1 | 4 Cores @ 2.70 GHz |
| Cluster 2 | 3 Cores @ 3.50 GHz |
| Cluster 3 | 1 Core @ 4.21 GHz |
| Memory Information | |
|---|---|
| Size | 11.09 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
403
75.0 IPS |
|
|
Image Classification (HP)
|
100% |
408
75.9 IPS |
|
|
Image Classification (Q)
|
99% |
1144
213.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
534
8.66 IPS |
|
|
Image Segmentation (HP)
|
100% |
540
8.75 IPS |
|
|
Image Segmentation (Q)
|
98% |
1086
17.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
708
0.83 IPS |
|
|
Pose Estimation (HP)
|
100% |
702
0.82 IPS |
|
|
Pose Estimation (Q)
|
98% |
2456
2.88 IPS |
|
|
Object Detection (SP)
|
100% |
352
27.9 IPS |
|
|
Object Detection (HP)
|
100% |
357
28.3 IPS |
|
|
Object Detection (Q)
|
87% |
1031
82.7 IPS |
|
|
Face Detection (SP)
|
100% |
808
9.60 IPS |
|
|
Face Detection (HP)
|
100% |
818
9.72 IPS |
|
|
Face Detection (Q)
|
97% |
2000
23.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
728
5.61 IPS |
|
|
Depth Estimation (HP)
|
99% |
732
5.64 IPS |
|
|
Depth Estimation (Q)
|
64% |
1822
16.5 IPS |
|
|
Style Transfer (SP)
|
100% |
1073
1.38 IPS |
|
|
Style Transfer (HP)
|
100% |
1077
1.38 IPS |
|
|
Style Transfer (Q)
|
98% |
2898
3.74 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
438
16.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
437
16.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1611
59.7 IPS |
|
|
Text Classification (SP)
|
100% |
594
793.4 IPS |
|
|
Text Classification (HP)
|
100% |
592
790.2 IPS |
|
|
Text Classification (Q)
|
91% |
807
1.09 KIPS |
|
|
Machine Translation (SP)
|
100% |
781
13.4 IPS |
|
|
Machine Translation (HP)
|
100% |
773
13.3 IPS |
|
|
Machine Translation (Q)
|
57% |
539
13.2 IPS |
