vivo V2324HA
Geekbench ML Score
1320
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 02:24 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2324HA |
| Model ID | vivo V2324HA |
| 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 @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 14.95 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
874
163.5 IPS |
|
|
Image Classification (F16)
|
100% |
899
168.2 IPS |
|
|
Image Classification (I8)
|
97% |
1465
274.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
980
16.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
956
16.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
950
15.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
1470
1.78 IPS |
|
|
Pose Estimation (F16)
|
100% |
1396
1.69 IPS |
|
|
Pose Estimation (I8)
|
100% |
6031
7.30 IPS |
|
|
Object Detection (F32)
|
100% |
620
46.3 IPS |
|
|
Object Detection (F16)
|
100% |
603
45.0 IPS |
|
|
Object Detection (I8)
|
61% |
1066
79.6 IPS |
|
|
Face Detection (F32)
|
100% |
1581
18.8 IPS |
|
|
Face Detection (F16)
|
100% |
1615
19.2 IPS |
|
|
Face Detection (I8)
|
86% |
1975
23.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1512
11.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
1475
11.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
2172
16.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2194
2.89 IPS |
|
|
Style Transfer (F16)
|
100% |
2121
2.79 IPS |
|
|
Style Transfer (I8)
|
98% |
4418
5.81 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
931
33.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
942
33.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2300
82.1 IPS |
|
|
Text Classification (F32)
|
100% |
907
1.30 KIPS |
|
|
Text Classification (F16)
|
100% |
927
1.33 KIPS |
|
|
Text Classification (I8)
|
92% |
729
1.05 KIPS |
|
|
Machine Translation (F32)
|
100% |
1565
28.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1580
29.1 IPS |
|
|
Machine Translation (I8)
|
64% |
541
9.96 IPS |
