vivo V2309
Geekbench ML Score
1300
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 06:15 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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
769
144.0 IPS |
|
|
Image Classification (F16)
|
100% |
858
160.5 IPS |
|
|
Image Classification (I8)
|
97% |
1327
248.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
1046
17.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1044
17.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
1265
21.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1283
1.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
1310
1.59 IPS |
|
|
Pose Estimation (I8)
|
100% |
5772
6.99 IPS |
|
|
Object Detection (F32)
|
100% |
631
47.1 IPS |
|
|
Object Detection (F16)
|
100% |
626
46.7 IPS |
|
|
Object Detection (I8)
|
61% |
1010
75.4 IPS |
|
|
Face Detection (F32)
|
100% |
1625
19.3 IPS |
|
|
Face Detection (F16)
|
100% |
1545
18.4 IPS |
|
|
Face Detection (I8)
|
86% |
2235
26.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
1427
11.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
1359
10.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
2384
18.5 IPS |
|
|
Style Transfer (F32)
|
100% |
2101
2.76 IPS |
|
|
Style Transfer (F16)
|
100% |
2139
2.81 IPS |
|
|
Style Transfer (I8)
|
98% |
4661
6.13 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
899
32.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
918
32.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2484
88.7 IPS |
|
|
Text Classification (F32)
|
100% |
893
1.28 KIPS |
|
|
Text Classification (F16)
|
100% |
864
1.24 KIPS |
|
|
Text Classification (I8)
|
92% |
586
842.5 IPS |
|
|
Machine Translation (F32)
|
100% |
1461
26.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1447
26.6 IPS |
|
|
Machine Translation (I8)
|
64% |
531
9.77 IPS |
