vivo V2324HA
Geekbench ML Score
3434
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 08:30 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% |
972
181.8 IPS |
|
|
Image Classification (F16)
|
100% |
4525
846.8 IPS |
|
|
Image Classification (I8)
|
97% |
9452
1.77 KIPS |
|
|
Image Segmentation (F32)
|
100% |
646
10.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
4175
69.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
1792
29.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
8925
10.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
17606
21.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
65709
79.6 IPS |
|
|
Object Detection (F32)
|
100% |
690
51.5 IPS |
|
|
Object Detection (F16)
|
100% |
2858
213.4 IPS |
|
|
Object Detection (I8)
|
64% |
3279
244.8 IPS |
|
|
Face Detection (F32)
|
100% |
3412
40.6 IPS |
|
|
Face Detection (F16)
|
97% |
12293
146.2 IPS |
|
|
Face Detection (I8)
|
86% |
11489
136.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
927
7.19 IPS |
|
|
Depth Estimation (F16)
|
100% |
13912
107.9 IPS |
|
|
Depth Estimation (I8)
|
95% |
25947
201.2 IPS |
|
|
Style Transfer (F32)
|
100% |
2532
3.33 IPS |
|
|
Style Transfer (F16)
|
100% |
2405
3.16 IPS |
|
|
Style Transfer (I8)
|
31% |
4683
6.16 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2225
79.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11207
400.2 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
32991
1.18 KIPS |
|
|
Text Classification (F32)
|
100% |
124
177.9 IPS |
|
|
Text Classification (F16)
|
100% |
1977
2.84 KIPS |
|
|
Text Classification (I8)
|
76% |
2019
2.90 KIPS |
|
|
Machine Translation (F32)
|
100% |
389
7.15 IPS |
|
|
Machine Translation (F16)
|
100% |
2186
40.2 IPS |
|
|
Machine Translation (I8)
|
76% |
556
10.2 IPS |
