vivo V2301A
Geekbench ML Score
709
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 17 2024 05:01 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2301A |
| Model ID | vivo V2301A |
| 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 | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.50 GHz |
| Cluster 3 | 1 Core @ 3.00 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% |
317
59.3 IPS |
|
|
Image Classification (F16)
|
100% |
323
60.4 IPS |
|
|
Image Classification (I8)
|
97% |
578
108.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
457
7.64 IPS |
|
|
Image Segmentation (F16)
|
100% |
483
8.07 IPS |
|
|
Image Segmentation (I8)
|
98% |
526
8.79 IPS |
|
|
Pose Estimation (F32)
|
100% |
910
1.10 IPS |
|
|
Pose Estimation (F16)
|
100% |
831
1.01 IPS |
|
|
Pose Estimation (I8)
|
100% |
3250
3.94 IPS |
|
|
Object Detection (F32)
|
100% |
338
25.3 IPS |
|
|
Object Detection (F16)
|
100% |
337
25.2 IPS |
|
|
Object Detection (I8)
|
61% |
599
44.7 IPS |
|
|
Face Detection (F32)
|
100% |
819
9.74 IPS |
|
|
Face Detection (F16)
|
100% |
809
9.62 IPS |
|
|
Face Detection (I8)
|
86% |
1178
14.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
783
6.07 IPS |
|
|
Depth Estimation (F16)
|
100% |
804
6.24 IPS |
|
|
Depth Estimation (I8)
|
95% |
1737
13.5 IPS |
|
|
Style Transfer (F32)
|
100% |
1686
2.22 IPS |
|
|
Style Transfer (F16)
|
100% |
1596
2.10 IPS |
|
|
Style Transfer (I8)
|
98% |
3033
3.99 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
537
19.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
540
19.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1510
53.9 IPS |
|
|
Text Classification (F32)
|
100% |
415
596.2 IPS |
|
|
Text Classification (F16)
|
100% |
396
569.0 IPS |
|
|
Text Classification (I8)
|
92% |
315
453.1 IPS |
|
|
Machine Translation (F32)
|
100% |
746
13.7 IPS |
|
|
Machine Translation (F16)
|
100% |
760
14.0 IPS |
|
|
Machine Translation (I8)
|
64% |
329
6.06 IPS |
