vivo V2347
Geekbench ML Score
924
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 15 2024 07:00 PM |
| Views | 1 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
316
59.1 IPS |
|
|
Image Classification (F16)
|
100% |
281
52.6 IPS |
|
|
Image Classification (I8)
|
97% |
260
48.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
1197
20.0 IPS |
|
|
Image Segmentation (F16)
|
100% |
1208
20.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
1200
20.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
827
1.00 IPS |
|
|
Pose Estimation (F16)
|
100% |
1188
1.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
1177
1.43 IPS |
|
|
Object Detection (F32)
|
100% |
311
23.3 IPS |
|
|
Object Detection (F16)
|
100% |
415
31.0 IPS |
|
|
Object Detection (I8)
|
62% |
428
31.9 IPS |
|
|
Face Detection (F32)
|
100% |
1798
21.4 IPS |
|
|
Face Detection (F16)
|
98% |
2015
24.0 IPS |
|
|
Face Detection (I8)
|
86% |
1860
22.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1497
11.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
1733
13.4 IPS |
|
|
Depth Estimation (I8)
|
95% |
1731
13.4 IPS |
|
|
Style Transfer (F32)
|
100% |
4037
5.31 IPS |
|
|
Style Transfer (F16)
|
100% |
5396
7.10 IPS |
|
|
Style Transfer (I8)
|
98% |
5320
7.00 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
702
25.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
890
31.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
918
32.8 IPS |
|
|
Text Classification (F32)
|
100% |
397
569.9 IPS |
|
|
Text Classification (F16)
|
100% |
391
562.0 IPS |
|
|
Text Classification (I8)
|
92% |
588
844.4 IPS |
|
|
Machine Translation (F32)
|
100% |
585
10.8 IPS |
|
|
Machine Translation (F16)
|
100% |
587
10.8 IPS |
|
|
Machine Translation (I8)
|
64% |
579
10.7 IPS |
