vivo V2324A
Geekbench ML Score
3287
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 09 2024 05:57 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | vivo V2324A |
| Model ID | vivo V2324A |
| 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 @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 14.96 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1005
188.1 IPS |
|
|
Image Classification (F16)
|
100% |
4267
798.5 IPS |
|
|
Image Classification (I8)
|
97% |
8264
1.55 KIPS |
|
|
Image Segmentation (F32)
|
100% |
645
10.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
4009
67.0 IPS |
|
|
Image Segmentation (I8)
|
98% |
1778
29.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
8380
10.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
17790
21.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
68726
83.2 IPS |
|
|
Object Detection (F32)
|
100% |
670
50.0 IPS |
|
|
Object Detection (F16)
|
100% |
2859
213.4 IPS |
|
|
Object Detection (I8)
|
64% |
3231
241.2 IPS |
|
|
Face Detection (F32)
|
100% |
3407
40.5 IPS |
|
|
Face Detection (F16)
|
97% |
11627
138.2 IPS |
|
|
Face Detection (I8)
|
86% |
11275
134.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
924
7.16 IPS |
|
|
Depth Estimation (F16)
|
100% |
14583
113.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
26495
205.5 IPS |
|
|
Style Transfer (F32)
|
100% |
2520
3.31 IPS |
|
|
Style Transfer (F16)
|
100% |
2387
3.14 IPS |
|
|
Style Transfer (I8)
|
31% |
4665
6.14 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2183
78.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10587
378.1 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
29634
1.06 KIPS |
|
|
Text Classification (F32)
|
100% |
105
151.6 IPS |
|
|
Text Classification (F16)
|
100% |
1710
2.46 KIPS |
|
|
Text Classification (I8)
|
76% |
1339
1.93 KIPS |
|
|
Machine Translation (F32)
|
100% |
324
5.97 IPS |
|
|
Machine Translation (F16)
|
100% |
1979
36.4 IPS |
|
|
Machine Translation (I8)
|
76% |
658
12.1 IPS |
