vivo V2309
Geekbench ML Score
1003
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 06:18 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2309 |
| Model ID | vivo V2309 |
| Motherboard | k6989v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 14.96 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
531
99.4 IPS |
|
|
Image Classification (F16)
|
100% |
660
123.6 IPS |
|
|
Image Classification (I8)
|
97% |
636
119.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
1221
20.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
1308
21.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
1255
21.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
676
0.82 IPS |
|
|
Pose Estimation (F16)
|
100% |
1023
1.24 IPS |
|
|
Pose Estimation (I8)
|
100% |
1022
1.24 IPS |
|
|
Object Detection (F32)
|
100% |
455
33.9 IPS |
|
|
Object Detection (F16)
|
100% |
652
48.6 IPS |
|
|
Object Detection (I8)
|
62% |
533
39.8 IPS |
|
|
Face Detection (F32)
|
100% |
2045
24.3 IPS |
|
|
Face Detection (F16)
|
98% |
2124
25.2 IPS |
|
|
Face Detection (I8)
|
86% |
2046
24.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
1354
10.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
1653
12.8 IPS |
|
|
Depth Estimation (I8)
|
95% |
1661
12.9 IPS |
|
|
Style Transfer (F32)
|
100% |
3785
4.98 IPS |
|
|
Style Transfer (F16)
|
100% |
4807
6.32 IPS |
|
|
Style Transfer (I8)
|
98% |
4816
6.34 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
756
27.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
917
32.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
902
32.2 IPS |
|
|
Text Classification (F32)
|
100% |
356
511.3 IPS |
|
|
Text Classification (F16)
|
100% |
358
514.3 IPS |
|
|
Text Classification (I8)
|
92% |
570
818.8 IPS |
|
|
Machine Translation (F32)
|
100% |
517
9.52 IPS |
|
|
Machine Translation (F16)
|
100% |
520
9.57 IPS |
|
|
Machine Translation (I8)
|
64% |
633
11.6 IPS |
