vivo V2324A
Geekbench ML Score
3434
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 07 2024 07:53 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| 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 | 11.05 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
995
186.2 IPS |
|
|
Image Classification (F16)
|
100% |
4548
851.0 IPS |
|
|
Image Classification (I8)
|
97% |
9125
1.71 KIPS |
|
|
Image Segmentation (F32)
|
100% |
650
10.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
4148
69.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1792
29.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
8378
10.1 IPS |
|
|
Pose Estimation (F16)
|
100% |
17776
21.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
72077
87.3 IPS |
|
|
Object Detection (F32)
|
100% |
689
51.4 IPS |
|
|
Object Detection (F16)
|
100% |
2920
218.0 IPS |
|
|
Object Detection (I8)
|
64% |
3310
247.1 IPS |
|
|
Face Detection (F32)
|
100% |
3524
41.9 IPS |
|
|
Face Detection (F16)
|
97% |
12212
145.2 IPS |
|
|
Face Detection (I8)
|
86% |
11397
135.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
935
7.25 IPS |
|
|
Depth Estimation (F16)
|
100% |
13354
103.6 IPS |
|
|
Depth Estimation (I8)
|
95% |
28001
217.2 IPS |
|
|
Style Transfer (F32)
|
100% |
2547
3.35 IPS |
|
|
Style Transfer (F16)
|
100% |
2423
3.19 IPS |
|
|
Style Transfer (I8)
|
31% |
4684
6.16 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2401
85.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10950
391.1 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
32709
1.17 KIPS |
|
|
Text Classification (F32)
|
100% |
122
175.7 IPS |
|
|
Text Classification (F16)
|
100% |
1964
2.82 KIPS |
|
|
Text Classification (I8)
|
76% |
1699
2.44 KIPS |
|
|
Machine Translation (F32)
|
100% |
389
7.16 IPS |
|
|
Machine Translation (F16)
|
100% |
2230
41.0 IPS |
|
|
Machine Translation (I8)
|
76% |
556
10.2 IPS |
