vivo V2324HA
Geekbench ML Score
3418
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 06:14 AM |
| Views | 1 |
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% |
901
168.6 IPS |
|
|
Image Classification (F16)
|
100% |
4575
856.0 IPS |
|
|
Image Classification (I8)
|
97% |
9312
1.74 KIPS |
|
|
Image Segmentation (F32)
|
100% |
647
10.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
4128
68.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
1794
30.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
8949
10.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
17572
21.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
69522
84.2 IPS |
|
|
Object Detection (F32)
|
100% |
658
49.1 IPS |
|
|
Object Detection (F16)
|
100% |
2893
216.0 IPS |
|
|
Object Detection (I8)
|
64% |
3269
244.1 IPS |
|
|
Face Detection (F32)
|
100% |
3429
40.8 IPS |
|
|
Face Detection (F16)
|
97% |
12140
144.3 IPS |
|
|
Face Detection (I8)
|
86% |
11487
136.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
920
7.14 IPS |
|
|
Depth Estimation (F16)
|
100% |
13748
106.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
28447
220.6 IPS |
|
|
Style Transfer (F32)
|
100% |
2543
3.35 IPS |
|
|
Style Transfer (F16)
|
100% |
2401
3.16 IPS |
|
|
Style Transfer (I8)
|
31% |
4676
6.15 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2150
76.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11220
400.7 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
34227
1.22 KIPS |
|
|
Text Classification (F32)
|
100% |
127
182.2 IPS |
|
|
Text Classification (F16)
|
100% |
1767
2.54 KIPS |
|
|
Text Classification (I8)
|
76% |
1956
2.81 KIPS |
|
|
Machine Translation (F32)
|
100% |
392
7.21 IPS |
|
|
Machine Translation (F16)
|
100% |
2169
39.9 IPS |
|
|
Machine Translation (I8)
|
76% |
546
10.0 IPS |
