vivo V2324HA
Geekbench ML Score
3439
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | September 26 2024 08:27 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% |
1003
187.7 IPS |
|
|
Image Classification (F16)
|
100% |
4550
851.5 IPS |
|
|
Image Classification (I8)
|
97% |
9335
1.75 KIPS |
|
|
Image Segmentation (F32)
|
100% |
650
10.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
4152
69.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1793
29.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
8470
10.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
17762
21.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
67893
82.2 IPS |
|
|
Object Detection (F32)
|
100% |
694
51.8 IPS |
|
|
Object Detection (F16)
|
100% |
2936
219.2 IPS |
|
|
Object Detection (I8)
|
64% |
3278
244.7 IPS |
|
|
Face Detection (F32)
|
100% |
3491
41.5 IPS |
|
|
Face Detection (F16)
|
97% |
12462
148.2 IPS |
|
|
Face Detection (I8)
|
86% |
11472
136.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
926
7.18 IPS |
|
|
Depth Estimation (F16)
|
100% |
14569
113.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
28166
218.4 IPS |
|
|
Style Transfer (F32)
|
100% |
2555
3.36 IPS |
|
|
Style Transfer (F16)
|
100% |
2405
3.16 IPS |
|
|
Style Transfer (I8)
|
31% |
4699
6.18 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2276
81.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11272
402.5 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
32443
1.16 KIPS |
|
|
Text Classification (F32)
|
100% |
124
177.8 IPS |
|
|
Text Classification (F16)
|
100% |
1815
2.61 KIPS |
|
|
Text Classification (I8)
|
76% |
1805
2.59 KIPS |
|
|
Machine Translation (F32)
|
100% |
390
7.18 IPS |
|
|
Machine Translation (F16)
|
100% |
2193
40.4 IPS |
|
|
Machine Translation (I8)
|
76% |
561
10.3 IPS |
