vivo V2347
Geekbench ML Score
2179
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 15 2024 07:04 PM |
| Views | 27 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2347 |
| Model ID | vivo V2347 |
| Motherboard | k6985v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 3.00 GHz |
| Cluster 3 | 1 Core @ 3.35 GHz |
| Memory Information | |
|---|---|
| Size | 11.07 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
614
115.0 IPS |
|
|
Image Classification (F16)
|
100% |
2612
488.7 IPS |
|
|
Image Classification (I8)
|
97% |
6596
1.23 KIPS |
|
|
Image Segmentation (F32)
|
100% |
379
6.33 IPS |
|
|
Image Segmentation (F16)
|
100% |
2543
42.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
1229
20.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
2986
3.62 IPS |
|
|
Pose Estimation (F16)
|
100% |
7878
9.54 IPS |
|
|
Pose Estimation (I8)
|
100% |
31955
38.7 IPS |
|
|
Object Detection (F32)
|
100% |
484
36.1 IPS |
|
|
Object Detection (F16)
|
100% |
1965
146.7 IPS |
|
|
Object Detection (I8)
|
64% |
2816
210.2 IPS |
|
|
Face Detection (F32)
|
25% |
708
8.41 IPS |
|
|
Face Detection (F16)
|
97% |
6927
82.4 IPS |
|
|
Face Detection (I8)
|
86% |
10280
122.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
989
7.67 IPS |
|
|
Depth Estimation (F16)
|
100% |
9934
77.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
28465
220.7 IPS |
|
|
Style Transfer (F32)
|
100% |
2326
3.06 IPS |
|
|
Style Transfer (F16)
|
100% |
2916
3.84 IPS |
|
|
Style Transfer (I8)
|
31% |
6535
8.60 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1256
44.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
5535
197.7 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
17561
627.2 IPS |
|
|
Text Classification (F32)
|
100% |
64
92.1 IPS |
|
|
Text Classification (F16)
|
100% |
1253
1.80 KIPS |
|
|
Text Classification (I8)
|
92% |
942
1.35 KIPS |
|
|
Machine Translation (F32)
|
100% |
316
5.82 IPS |
|
|
Machine Translation (F16)
|
100% |
610
11.2 IPS |
|
|
Machine Translation (I8)
|
76% |
506
9.32 IPS |
