vivo V2515
Geekbench AI Score
1271
Single Precision Score
1792
Half Precision Score
1523
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 03 2025 12:51 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | vivo V2515 |
| Model ID | vivo V2515 |
| 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% |
646
120.2 IPS |
|
|
Image Classification (HP)
|
100% |
1379
256.4 IPS |
|
|
Image Classification (Q)
|
97% |
935
174.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1722
27.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2726
44.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2404
39.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
8254
9.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
14807
17.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
14364
16.8 IPS |
|
|
Object Detection (SP)
|
100% |
512
40.6 IPS |
|
|
Object Detection (HP)
|
99% |
799
63.4 IPS |
|
|
Object Detection (Q)
|
83% |
788
63.7 IPS |
|
|
Face Detection (SP)
|
100% |
3002
35.7 IPS |
|
|
Face Detection (HP)
|
100% |
3578
42.5 IPS |
|
|
Face Detection (Q)
|
96% |
3966
47.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
3287
25.3 IPS |
|
|
Depth Estimation (HP)
|
98% |
5147
39.8 IPS |
|
|
Depth Estimation (Q)
|
62% |
4193
39.8 IPS |
|
|
Style Transfer (SP)
|
100% |
13399
17.2 IPS |
|
|
Style Transfer (HP)
|
100% |
23212
29.8 IPS |
|
|
Style Transfer (Q)
|
98% |
22105
28.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1779
65.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2231
82.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2480
91.9 IPS |
|
|
Text Classification (SP)
|
35% |
24
216.0 IPS |
|
|
Text Classification (HP)
|
29% |
17
285.2 IPS |
|
|
Text Classification (Q)
|
32% |
25
324.2 IPS |
|
|
Machine Translation (SP)
|
100% |
417
7.19 IPS |
|
|
Machine Translation (HP)
|
100% |
476
8.19 IPS |
|
|
Machine Translation (Q)
|
43% |
116
6.73 IPS |
