vivo V2307A
Geekbench ML Score
965
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 30 2025 02:17 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | vivo V2307A |
| Model ID | vivo V2307A |
| 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 | 14.85 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
495
92.7 IPS |
|
|
Image Classification (F16)
|
100% |
502
93.9 IPS |
|
|
Image Classification (I8)
|
97% |
875
163.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
624
10.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
617
10.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
609
10.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1320
1.60 IPS |
|
|
Pose Estimation (F16)
|
100% |
1247
1.51 IPS |
|
|
Pose Estimation (I8)
|
100% |
4516
5.47 IPS |
|
|
Object Detection (F32)
|
100% |
526
39.3 IPS |
|
|
Object Detection (F16)
|
100% |
477
35.6 IPS |
|
|
Object Detection (I8)
|
61% |
733
54.7 IPS |
|
|
Face Detection (F32)
|
100% |
1007
12.0 IPS |
|
|
Face Detection (F16)
|
100% |
1032
12.3 IPS |
|
|
Face Detection (I8)
|
86% |
1615
19.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
1043
8.09 IPS |
|
|
Depth Estimation (F16)
|
100% |
1024
7.94 IPS |
|
|
Depth Estimation (I8)
|
95% |
1425
11.0 IPS |
|
|
Style Transfer (F32)
|
100% |
2168
2.85 IPS |
|
|
Style Transfer (F16)
|
100% |
2225
2.93 IPS |
|
|
Style Transfer (I8)
|
98% |
4408
5.80 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
858
30.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
838
29.9 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2015
72.0 IPS |
|
|
Text Classification (F32)
|
100% |
553
794.3 IPS |
|
|
Text Classification (F16)
|
100% |
531
763.2 IPS |
|
|
Text Classification (I8)
|
92% |
374
537.7 IPS |
|
|
Machine Translation (F32)
|
100% |
1283
23.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1223
22.5 IPS |
|
|
Machine Translation (I8)
|
64% |
364
6.70 IPS |
