vivo V2515
Geekbench AI Score
1438
Single Precision Score
1838
Half Precision Score
1546
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | December 04 2025 04:57 AM |
| Views | 6 |
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 | 15.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
715
133.0 IPS |
|
|
Image Classification (HP)
|
100% |
818
152.1 IPS |
|
|
Image Classification (Q)
|
97% |
741
138.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
2269
36.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2682
43.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
2494
40.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
11182
13.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
18029
21.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
18821
22.1 IPS |
|
|
Object Detection (SP)
|
100% |
527
41.8 IPS |
|
|
Object Detection (HP)
|
99% |
775
61.5 IPS |
|
|
Object Detection (Q)
|
83% |
730
59.0 IPS |
|
|
Face Detection (SP)
|
100% |
3296
39.2 IPS |
|
|
Face Detection (HP)
|
100% |
3991
47.4 IPS |
|
|
Face Detection (Q)
|
96% |
4257
50.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
3972
30.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
6629
51.2 IPS |
|
|
Depth Estimation (Q)
|
62% |
4519
42.9 IPS |
|
|
Style Transfer (SP)
|
100% |
15640
20.1 IPS |
|
|
Style Transfer (HP)
|
100% |
26013
33.4 IPS |
|
|
Style Transfer (Q)
|
98% |
25506
32.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1908
70.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2503
92.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2333
86.5 IPS |
|
|
Text Classification (SP)
|
35% |
25
223.4 IPS |
|
|
Text Classification (HP)
|
29% |
18
309.7 IPS |
|
|
Text Classification (Q)
|
32% |
25
320.4 IPS |
|
|
Machine Translation (SP)
|
100% |
406
6.99 IPS |
|
|
Machine Translation (HP)
|
100% |
465
8.02 IPS |
|
|
Machine Translation (Q)
|
43% |
108
6.30 IPS |
