vivo V2329A
Geekbench ML Score
842
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | June 18 2025 06:46 AM |
| Views | 3 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2329A |
| Model ID | vivo V2329A |
| Motherboard | pineapple |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.26 GHz |
| Cluster 1 | 2 Cores @ 2.27 GHz |
| Cluster 2 | 2 Cores @ 2.96 GHz |
| Cluster 3 | 3 Cores @ 3.15 GHz |
| Cluster 4 | 1 Core @ 3.30 GHz |
| Memory Information | |
|---|---|
| Size | 14.90 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
383
71.7 IPS |
|
|
Image Classification (F16)
|
100% |
409
76.5 IPS |
|
|
Image Classification (I8)
|
97% |
666
124.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
527
8.81 IPS |
|
|
Image Segmentation (F16)
|
100% |
509
8.50 IPS |
|
|
Image Segmentation (I8)
|
98% |
540
9.02 IPS |
|
|
Pose Estimation (F32)
|
100% |
1135
1.37 IPS |
|
|
Pose Estimation (F16)
|
100% |
1070
1.30 IPS |
|
|
Pose Estimation (I8)
|
100% |
4744
5.75 IPS |
|
|
Object Detection (F32)
|
100% |
401
29.9 IPS |
|
|
Object Detection (F16)
|
100% |
419
31.3 IPS |
|
|
Object Detection (I8)
|
61% |
705
52.6 IPS |
|
|
Face Detection (F32)
|
100% |
975
11.6 IPS |
|
|
Face Detection (F16)
|
100% |
1001
11.9 IPS |
|
|
Face Detection (I8)
|
86% |
1445
17.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
996
7.72 IPS |
|
|
Depth Estimation (F16)
|
100% |
1050
8.15 IPS |
|
|
Depth Estimation (I8)
|
95% |
1759
13.6 IPS |
|
|
Style Transfer (F32)
|
100% |
2056
2.70 IPS |
|
|
Style Transfer (F16)
|
100% |
2048
2.69 IPS |
|
|
Style Transfer (I8)
|
98% |
4691
6.17 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
672
24.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
707
25.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1731
61.8 IPS |
|
|
Text Classification (F32)
|
100% |
360
517.5 IPS |
|
|
Text Classification (F16)
|
100% |
422
606.1 IPS |
|
|
Text Classification (I8)
|
92% |
330
474.8 IPS |
|
|
Machine Translation (F32)
|
100% |
1009
18.6 IPS |
|
|
Machine Translation (F16)
|
100% |
905
16.6 IPS |
|
|
Machine Translation (I8)
|
64% |
297
5.47 IPS |
