vivo V2408A
Geekbench ML Score
1906
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | November 02 2024 10:04 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | vivo V2408A |
| Model ID | vivo V2408A |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | Qualcomm ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 3 part 1 revision 4 |
| Base Frequency | 3.53 GHz |
| Cluster 1 | 6 Cores @ 3.53 GHz |
| Cluster 2 | 2 Cores @ 4.32 GHz |
| Memory Information | |
|---|---|
| Size | 10.87 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1151
215.4 IPS |
|
|
Image Classification (F16)
|
100% |
1148
214.8 IPS |
|
|
Image Classification (I8)
|
97% |
1517
283.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1481
24.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
1479
24.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
1529
25.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
2198
2.66 IPS |
|
|
Pose Estimation (F16)
|
100% |
2156
2.61 IPS |
|
|
Pose Estimation (I8)
|
100% |
8388
10.2 IPS |
|
|
Object Detection (F32)
|
100% |
1126
84.1 IPS |
|
|
Object Detection (F16)
|
100% |
1124
83.9 IPS |
|
|
Object Detection (I8)
|
61% |
2068
154.4 IPS |
|
|
Face Detection (F32)
|
100% |
2491
29.6 IPS |
|
|
Face Detection (F16)
|
100% |
2466
29.3 IPS |
|
|
Face Detection (I8)
|
86% |
3776
44.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
2372
18.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
2384
18.5 IPS |
|
|
Depth Estimation (I8)
|
95% |
3967
30.8 IPS |
|
|
Style Transfer (F32)
|
100% |
3443
4.53 IPS |
|
|
Style Transfer (F16)
|
100% |
3448
4.54 IPS |
|
|
Style Transfer (I8)
|
98% |
8351
11.0 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1171
41.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1183
42.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
3460
123.6 IPS |
|
|
Text Classification (F32)
|
100% |
890
1.28 KIPS |
|
|
Text Classification (F16)
|
100% |
895
1.29 KIPS |
|
|
Text Classification (I8)
|
92% |
707
1.02 KIPS |
|
|
Machine Translation (F32)
|
100% |
1782
32.8 IPS |
|
|
Machine Translation (F16)
|
100% |
1846
34.0 IPS |
|
|
Machine Translation (I8)
|
64% |
802
14.8 IPS |
