vivo V2405A
Geekbench ML Score
1154
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 18 2025 04:14 PM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | vivo V2405A |
| Model ID | vivo V2405A |
| Motherboard | k6991v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3461 revision 1 |
| Base Frequency | 2.40 GHz |
| Cluster 1 | 4 Cores @ 2.40 GHz |
| Cluster 2 | 3 Cores @ 3.30 GHz |
| Cluster 3 | 1 Core @ 3.63 GHz |
| Memory Information | |
|---|---|
| Size | 11.08 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
556
104.0 IPS |
|
|
Image Classification (F16)
|
100% |
557
104.3 IPS |
|
|
Image Classification (I8)
|
97% |
501
93.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
1089
18.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
1379
23.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1417
23.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
972
1.18 IPS |
|
|
Pose Estimation (F16)
|
100% |
1486
1.80 IPS |
|
|
Pose Estimation (I8)
|
100% |
1465
1.77 IPS |
|
|
Object Detection (F32)
|
100% |
531
39.7 IPS |
|
|
Object Detection (F16)
|
100% |
525
39.2 IPS |
|
|
Object Detection (I8)
|
62% |
496
37.0 IPS |
|
|
Face Detection (F32)
|
100% |
2253
26.8 IPS |
|
|
Face Detection (F16)
|
98% |
2620
31.1 IPS |
|
|
Face Detection (I8)
|
86% |
2347
27.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
1564
12.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
2006
15.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
1981
15.4 IPS |
|
|
Style Transfer (F32)
|
100% |
4435
5.83 IPS |
|
|
Style Transfer (F16)
|
100% |
6404
8.42 IPS |
|
|
Style Transfer (I8)
|
98% |
6372
8.38 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
791
28.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
962
34.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
945
33.7 IPS |
|
|
Text Classification (F32)
|
100% |
492
706.5 IPS |
|
|
Text Classification (F16)
|
100% |
488
701.1 IPS |
|
|
Text Classification (I8)
|
92% |
679
975.2 IPS |
|
|
Machine Translation (F32)
|
100% |
804
14.8 IPS |
|
|
Machine Translation (F16)
|
100% |
783
14.4 IPS |
|
|
Machine Translation (I8)
|
64% |
668
12.3 IPS |
