vivo V2046A
Geekbench ML Score
506
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 04 2025 10:46 AM |
| Views | 8 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | vivo V2046A |
| Model ID | vivo V2046A |
| Motherboard | s5e9815 |
| Governor | energy_step |
| CPU Information | |
|---|---|
| Name | ARM Samsung |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.60 GHz |
| Cluster 3 | 1 Core @ 2.81 GHz |
| Memory Information | |
|---|---|
| Size | 7.11 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
266
49.8 IPS |
|
|
Image Classification (F16)
|
100% |
256
47.9 IPS |
|
|
Image Classification (I8)
|
97% |
334
62.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
327
5.46 IPS |
|
|
Image Segmentation (F16)
|
100% |
338
5.65 IPS |
|
|
Image Segmentation (I8)
|
98% |
496
8.28 IPS |
|
|
Pose Estimation (F32)
|
100% |
559
0.68 IPS |
|
|
Pose Estimation (F16)
|
100% |
541
0.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
2493
3.02 IPS |
|
|
Object Detection (F32)
|
100% |
282
21.1 IPS |
|
|
Object Detection (F16)
|
100% |
293
21.9 IPS |
|
|
Object Detection (I8)
|
61% |
640
47.7 IPS |
|
|
Face Detection (F32)
|
100% |
603
7.17 IPS |
|
|
Face Detection (F16)
|
100% |
578
6.87 IPS |
|
|
Face Detection (I8)
|
86% |
1103
13.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
611
4.74 IPS |
|
|
Depth Estimation (F16)
|
100% |
614
4.76 IPS |
|
|
Depth Estimation (I8)
|
95% |
1215
9.42 IPS |
|
|
Style Transfer (F32)
|
100% |
1133
1.49 IPS |
|
|
Style Transfer (F16)
|
100% |
1051
1.38 IPS |
|
|
Style Transfer (I8)
|
98% |
2719
3.58 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
368
13.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
367
13.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1033
36.9 IPS |
|
|
Text Classification (F32)
|
100% |
318
456.7 IPS |
|
|
Text Classification (F16)
|
100% |
331
476.4 IPS |
|
|
Text Classification (I8)
|
92% |
271
389.0 IPS |
|
|
Machine Translation (F32)
|
100% |
257
4.72 IPS |
|
|
Machine Translation (F16)
|
100% |
243
4.46 IPS |
|
|
Machine Translation (I8)
|
64% |
201
3.71 IPS |
