vivo V2405A
Geekbench ML Score
1062
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 18 2025 03:11 PM |
| Views | 7 |
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% |
688
128.7 IPS |
|
|
Image Classification (F16)
|
100% |
605
113.2 IPS |
|
|
Image Classification (I8)
|
97% |
490
91.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
1113
18.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
1452
24.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1453
24.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
956
1.16 IPS |
|
|
Pose Estimation (F16)
|
100% |
1458
1.77 IPS |
|
|
Pose Estimation (I8)
|
100% |
1050
1.27 IPS |
|
|
Object Detection (F32)
|
100% |
412
30.8 IPS |
|
|
Object Detection (F16)
|
100% |
488
36.4 IPS |
|
|
Object Detection (I8)
|
62% |
458
34.2 IPS |
|
|
Face Detection (F32)
|
100% |
1962
23.3 IPS |
|
|
Face Detection (F16)
|
98% |
2319
27.6 IPS |
|
|
Face Detection (I8)
|
86% |
2136
25.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
1270
9.85 IPS |
|
|
Depth Estimation (F16)
|
100% |
1595
12.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
1591
12.3 IPS |
|
|
Style Transfer (F32)
|
100% |
3695
4.86 IPS |
|
|
Style Transfer (F16)
|
100% |
4898
6.44 IPS |
|
|
Style Transfer (I8)
|
98% |
4886
6.43 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
730
26.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
857
30.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
832
29.7 IPS |
|
|
Text Classification (F32)
|
100% |
488
701.0 IPS |
|
|
Text Classification (F16)
|
100% |
490
704.0 IPS |
|
|
Text Classification (I8)
|
92% |
679
975.8 IPS |
|
|
Machine Translation (F32)
|
100% |
762
14.0 IPS |
|
|
Machine Translation (F16)
|
100% |
796
14.6 IPS |
|
|
Machine Translation (I8)
|
64% |
672
12.4 IPS |
