vivo V2502A
Geekbench AI Score
1475
Single Precision Score
1978
Half Precision Score
1576
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 14 2025 12:15 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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 | 15.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
526
97.8 IPS |
|
|
Image Classification (HP)
|
100% |
877
163.2 IPS |
|
|
Image Classification (Q)
|
97% |
712
132.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2211
35.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2874
46.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
2724
44.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
12019
14.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
19611
22.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
18663
21.9 IPS |
|
|
Object Detection (SP)
|
100% |
545
43.2 IPS |
|
|
Object Detection (HP)
|
99% |
896
71.0 IPS |
|
|
Object Detection (Q)
|
83% |
779
62.9 IPS |
|
|
Face Detection (SP)
|
100% |
2942
35.0 IPS |
|
|
Face Detection (HP)
|
100% |
4291
51.0 IPS |
|
|
Face Detection (Q)
|
96% |
3661
43.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
4774
36.8 IPS |
|
|
Depth Estimation (HP)
|
98% |
5978
46.2 IPS |
|
|
Depth Estimation (Q)
|
62% |
4683
44.5 IPS |
|
|
Style Transfer (SP)
|
100% |
17744
22.8 IPS |
|
|
Style Transfer (HP)
|
100% |
26191
33.7 IPS |
|
|
Style Transfer (Q)
|
98% |
27600
35.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1885
69.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2433
89.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2437
90.3 IPS |
|
|
Text Classification (SP)
|
35% |
32
294.1 IPS |
|
|
Text Classification (HP)
|
29% |
21
370.6 IPS |
|
|
Text Classification (Q)
|
32% |
26
331.4 IPS |
|
|
Machine Translation (SP)
|
100% |
426
7.33 IPS |
|
|
Machine Translation (HP)
|
100% |
606
10.4 IPS |
|
|
Machine Translation (Q)
|
43% |
112
6.53 IPS |
