vivo V2339A
Geekbench ML Score
3210
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:35 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2339A |
| Model ID | vivo V2339A |
| 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% |
663
124.1 IPS |
|
|
Image Classification (F16)
|
100% |
4490
840.2 IPS |
|
|
Image Classification (I8)
|
97% |
9137
1.71 KIPS |
|
|
Image Segmentation (F32)
|
100% |
610
10.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
4271
71.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1800
30.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
7285
8.82 IPS |
|
|
Pose Estimation (F16)
|
100% |
17761
21.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
69222
83.8 IPS |
|
|
Object Detection (F32)
|
100% |
533
39.8 IPS |
|
|
Object Detection (F16)
|
100% |
2954
220.5 IPS |
|
|
Object Detection (I8)
|
64% |
3312
247.3 IPS |
|
|
Face Detection (F32)
|
100% |
2848
33.9 IPS |
|
|
Face Detection (F16)
|
97% |
12252
145.7 IPS |
|
|
Face Detection (I8)
|
86% |
10462
124.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
873
6.77 IPS |
|
|
Depth Estimation (F16)
|
100% |
19361
150.1 IPS |
|
|
Depth Estimation (I8)
|
95% |
24130
187.1 IPS |
|
|
Style Transfer (F32)
|
100% |
2398
3.15 IPS |
|
|
Style Transfer (F16)
|
100% |
2373
3.12 IPS |
|
|
Style Transfer (I8)
|
31% |
4530
5.96 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1690
60.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11209
400.3 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
31840
1.14 KIPS |
|
|
Text Classification (F32)
|
100% |
100
144.3 IPS |
|
|
Text Classification (F16)
|
100% |
1979
2.84 KIPS |
|
|
Text Classification (I8)
|
76% |
1325
1.90 KIPS |
|
|
Machine Translation (F32)
|
100% |
339
6.25 IPS |
|
|
Machine Translation (F16)
|
100% |
2291
42.2 IPS |
|
|
Machine Translation (I8)
|
76% |
560
10.3 IPS |
