vivo V2232A
Geekbench ML Score
683
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | October 13 2024 02:13 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2232A |
| Model ID | vivo V2232A |
| Motherboard | taro |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 2 part 3400 revision 0 |
| Base Frequency | 2.02 GHz |
| Cluster 1 | 4 Cores @ 2.02 GHz |
| Cluster 2 | 3 Cores @ 2.75 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 11.01 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
330
61.7 IPS |
|
|
Image Classification (F16)
|
100% |
330
61.7 IPS |
|
|
Image Classification (I8)
|
97% |
550
102.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
479
8.01 IPS |
|
|
Image Segmentation (F16)
|
100% |
472
7.89 IPS |
|
|
Image Segmentation (I8)
|
98% |
548
9.15 IPS |
|
|
Pose Estimation (F32)
|
100% |
831
1.01 IPS |
|
|
Pose Estimation (F16)
|
100% |
807
0.98 IPS |
|
|
Pose Estimation (I8)
|
100% |
3398
4.11 IPS |
|
|
Object Detection (F32)
|
100% |
354
26.5 IPS |
|
|
Object Detection (F16)
|
100% |
340
25.4 IPS |
|
|
Object Detection (I8)
|
61% |
768
57.3 IPS |
|
|
Face Detection (F32)
|
100% |
740
8.80 IPS |
|
|
Face Detection (F16)
|
100% |
756
8.99 IPS |
|
|
Face Detection (I8)
|
86% |
1126
13.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
782
6.06 IPS |
|
|
Depth Estimation (F16)
|
100% |
773
5.99 IPS |
|
|
Depth Estimation (I8)
|
95% |
1450
11.2 IPS |
|
|
Style Transfer (F32)
|
100% |
1644
2.16 IPS |
|
|
Style Transfer (F16)
|
100% |
1607
2.11 IPS |
|
|
Style Transfer (I8)
|
98% |
2896
3.81 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
494
17.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
494
17.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1378
49.2 IPS |
|
|
Text Classification (F32)
|
100% |
397
570.2 IPS |
|
|
Text Classification (F16)
|
100% |
409
588.2 IPS |
|
|
Text Classification (I8)
|
92% |
215
309.6 IPS |
|
|
Machine Translation (F32)
|
100% |
709
13.0 IPS |
|
|
Machine Translation (F16)
|
100% |
701
12.9 IPS |
|
|
Machine Translation (I8)
|
64% |
292
5.37 IPS |
