vivo V2417A
Geekbench ML Score
1275
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 02 2024 02:35 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2417A |
| Model ID | vivo V2417A |
| 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 | 11.06 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
568
106.3 IPS |
|
|
Image Classification (F16)
|
100% |
791
148.0 IPS |
|
|
Image Classification (I8)
|
97% |
1141
213.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
1028
17.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
907
15.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
1143
19.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
1303
1.58 IPS |
|
|
Pose Estimation (F16)
|
100% |
1265
1.53 IPS |
|
|
Pose Estimation (I8)
|
100% |
5774
6.99 IPS |
|
|
Object Detection (F32)
|
100% |
701
52.3 IPS |
|
|
Object Detection (F16)
|
100% |
696
52.0 IPS |
|
|
Object Detection (I8)
|
61% |
1177
87.8 IPS |
|
|
Face Detection (F32)
|
100% |
1651
19.6 IPS |
|
|
Face Detection (F16)
|
100% |
1583
18.8 IPS |
|
|
Face Detection (I8)
|
86% |
2417
28.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1454
11.3 IPS |
|
|
Depth Estimation (F16)
|
100% |
1481
11.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
2493
19.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2219
2.92 IPS |
|
|
Style Transfer (F16)
|
100% |
2206
2.90 IPS |
|
|
Style Transfer (I8)
|
98% |
4631
6.09 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
929
33.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
930
33.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2528
90.3 IPS |
|
|
Text Classification (F32)
|
100% |
834
1.20 KIPS |
|
|
Text Classification (F16)
|
100% |
885
1.27 KIPS |
|
|
Text Classification (I8)
|
92% |
620
891.5 IPS |
|
|
Machine Translation (F32)
|
100% |
958
17.6 IPS |
|
|
Machine Translation (F16)
|
100% |
1360
25.0 IPS |
|
|
Machine Translation (I8)
|
64% |
497
9.14 IPS |
