vivo V2324HA
Geekbench ML Score
3358
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 08:13 AM |
| Views | 2 |
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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1013
189.6 IPS |
|
|
Image Classification (F16)
|
100% |
4546
850.6 IPS |
|
|
Image Classification (I8)
|
97% |
9326
1.75 KIPS |
|
|
Image Segmentation (F32)
|
100% |
649
10.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
4177
69.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
1794
30.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
8428
10.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
17838
21.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
68342
82.8 IPS |
|
|
Object Detection (F32)
|
100% |
696
51.9 IPS |
|
|
Object Detection (F16)
|
100% |
2963
221.2 IPS |
|
|
Object Detection (I8)
|
64% |
3271
244.2 IPS |
|
|
Face Detection (F32)
|
100% |
3452
41.0 IPS |
|
|
Face Detection (F16)
|
97% |
12491
148.5 IPS |
|
|
Face Detection (I8)
|
86% |
11541
137.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
928
7.20 IPS |
|
|
Depth Estimation (F16)
|
100% |
12490
96.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
28211
218.8 IPS |
|
|
Style Transfer (F32)
|
100% |
2550
3.35 IPS |
|
|
Style Transfer (F16)
|
100% |
2402
3.16 IPS |
|
|
Style Transfer (I8)
|
31% |
4685
6.16 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2190
78.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11377
406.3 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
31095
1.11 KIPS |
|
|
Text Classification (F32)
|
100% |
126
180.9 IPS |
|
|
Text Classification (F16)
|
100% |
1785
2.57 KIPS |
|
|
Text Classification (I8)
|
76% |
1092
1.57 KIPS |
|
|
Machine Translation (F32)
|
100% |
390
7.18 IPS |
|
|
Machine Translation (F16)
|
100% |
2188
40.3 IPS |
|
|
Machine Translation (I8)
|
76% |
553
10.2 IPS |
