vivo V2429
Geekbench AI Score
1955
Single Precision Score
3064
Half Precision Score
2477
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | November 20 2025 12:45 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | vivo V2429 |
| Model ID | vivo V2429 |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 14.86 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1228
228.4 IPS |
|
|
Image Classification (HP)
|
100% |
1822
338.9 IPS |
|
|
Image Classification (Q)
|
100% |
1650
306.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
2719
44.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
4701
76.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
3978
64.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
9845
11.5 IPS |
|
|
Pose Estimation (HP)
|
99% |
18145
21.2 IPS |
|
|
Pose Estimation (Q)
|
96% |
18391
21.5 IPS |
|
|
Object Detection (SP)
|
100% |
997
79.1 IPS |
|
|
Object Detection (HP)
|
99% |
1585
125.7 IPS |
|
|
Object Detection (Q)
|
87% |
1499
120.4 IPS |
|
|
Face Detection (SP)
|
100% |
3869
46.0 IPS |
|
|
Face Detection (HP)
|
100% |
6858
81.5 IPS |
|
|
Face Detection (Q)
|
97% |
5839
69.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
5112
39.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
7590
58.7 IPS |
|
|
Depth Estimation (Q)
|
61% |
6010
59.2 IPS |
|
|
Style Transfer (SP)
|
100% |
12674
16.3 IPS |
|
|
Style Transfer (HP)
|
100% |
26276
33.8 IPS |
|
|
Style Transfer (Q)
|
98% |
25857
33.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2695
99.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4597
169.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
4369
161.9 IPS |
|
|
Text Classification (SP)
|
35% |
47
456.8 IPS |
|
|
Text Classification (HP)
|
35% |
62
563.7 IPS |
|
|
Text Classification (Q)
|
33% |
48
580.1 IPS |
|
|
Machine Translation (SP)
|
100% |
786
13.5 IPS |
|
|
Machine Translation (HP)
|
97% |
761
13.2 IPS |
|
|
Machine Translation (Q)
|
43% |
253
14.4 IPS |
