vivo V2417A
Geekbench ML Score
997
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 12 2025 06:19 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
528
98.7 IPS |
|
|
Image Classification (F16)
|
100% |
680
127.2 IPS |
|
|
Image Classification (I8)
|
97% |
632
118.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
1214
20.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1263
21.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
1230
20.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
672
0.81 IPS |
|
|
Pose Estimation (F16)
|
100% |
1008
1.22 IPS |
|
|
Pose Estimation (I8)
|
100% |
1007
1.22 IPS |
|
|
Object Detection (F32)
|
100% |
404
30.2 IPS |
|
|
Object Detection (F16)
|
100% |
550
41.0 IPS |
|
|
Object Detection (I8)
|
62% |
561
41.9 IPS |
|
|
Face Detection (F32)
|
100% |
2295
27.3 IPS |
|
|
Face Detection (F16)
|
98% |
2086
24.8 IPS |
|
|
Face Detection (I8)
|
86% |
2197
26.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1349
10.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
1669
12.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
1678
13.0 IPS |
|
|
Style Transfer (F32)
|
100% |
3752
4.93 IPS |
|
|
Style Transfer (F16)
|
100% |
4779
6.29 IPS |
|
|
Style Transfer (I8)
|
98% |
4771
6.28 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
746
26.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
926
33.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
909
32.5 IPS |
|
|
Text Classification (F32)
|
100% |
355
510.2 IPS |
|
|
Text Classification (F16)
|
100% |
356
511.7 IPS |
|
|
Text Classification (I8)
|
92% |
569
817.1 IPS |
|
|
Machine Translation (F32)
|
100% |
517
9.51 IPS |
|
|
Machine Translation (F16)
|
100% |
517
9.52 IPS |
|
|
Machine Translation (I8)
|
64% |
617
11.4 IPS |
