vivo V2515
Geekbench AI Score
592
Single Precision Score
594
Half Precision Score
1358
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | February 07 2026 04:02 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| 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 |
| 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% |
363
67.4 IPS |
|
|
Image Classification (HP)
|
100% |
364
67.6 IPS |
|
|
Image Classification (Q)
|
99% |
1045
194.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
482
7.82 IPS |
|
|
Image Segmentation (HP)
|
100% |
483
7.83 IPS |
|
|
Image Segmentation (Q)
|
98% |
985
16.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
637
0.74 IPS |
|
|
Pose Estimation (HP)
|
100% |
634
0.74 IPS |
|
|
Pose Estimation (Q)
|
98% |
2601
3.05 IPS |
|
|
Object Detection (SP)
|
100% |
370
29.4 IPS |
|
|
Object Detection (HP)
|
100% |
374
29.7 IPS |
|
|
Object Detection (Q)
|
87% |
1080
86.6 IPS |
|
|
Face Detection (SP)
|
100% |
848
10.1 IPS |
|
|
Face Detection (HP)
|
100% |
852
10.1 IPS |
|
|
Face Detection (Q)
|
97% |
2009
24.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
723
5.57 IPS |
|
|
Depth Estimation (HP)
|
99% |
725
5.58 IPS |
|
|
Depth Estimation (Q)
|
64% |
1811
16.4 IPS |
|
|
Style Transfer (SP)
|
100% |
1057
1.36 IPS |
|
|
Style Transfer (HP)
|
100% |
1057
1.36 IPS |
|
|
Style Transfer (Q)
|
98% |
2912
3.75 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
435
16.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
436
16.1 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1621
60.1 IPS |
|
|
Text Classification (SP)
|
100% |
593
791.3 IPS |
|
|
Text Classification (HP)
|
100% |
597
796.6 IPS |
|
|
Text Classification (Q)
|
91% |
800
1.07 KIPS |
|
|
Machine Translation (SP)
|
100% |
774
13.3 IPS |
|
|
Machine Translation (HP)
|
100% |
781
13.5 IPS |
|
|
Machine Translation (Q)
|
57% |
539
13.2 IPS |
