vivo V2352A
Geekbench AI Score
990
Single Precision Score
1078
Half Precision Score
1500
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 16 2025 04:06 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | vivo V2352A |
| Model ID | vivo V2352A |
| 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 | 2.02 GHz |
| Cluster 1 | 3 Cores @ 2.02 GHz |
| Cluster 2 | 4 Cores @ 2.80 GHz |
| Cluster 3 | 1 Core @ 3.01 GHz |
| Memory Information | |
|---|---|
| Size | 11.03 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1469
273.1 IPS |
|
|
Image Classification (HP)
|
100% |
539
100.2 IPS |
|
|
Image Classification (Q)
|
100% |
1024
190.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
632
10.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
624
10.1 IPS |
|
|
Image Segmentation (Q)
|
98% |
1056
17.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
2937
3.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
3101
3.62 IPS |
|
|
Pose Estimation (Q)
|
84% |
2819
3.34 IPS |
|
|
Object Detection (SP)
|
98% |
514
40.9 IPS |
|
|
Object Detection (HP)
|
98% |
508
40.4 IPS |
|
|
Object Detection (Q)
|
83% |
860
69.5 IPS |
|
|
Face Detection (SP)
|
100% |
1071
12.7 IPS |
|
|
Face Detection (HP)
|
100% |
2712
32.2 IPS |
|
|
Face Detection (Q)
|
95% |
5430
64.8 IPS |
|
|
Depth Estimation (SP)
|
99% |
1454
11.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
2899
22.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
2146
19.7 IPS |
|
|
Style Transfer (SP)
|
89% |
2910
3.78 IPS |
|
|
Style Transfer (HP)
|
89% |
3217
4.18 IPS |
|
|
Style Transfer (Q)
|
98% |
5392
6.95 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
736
27.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
715
26.4 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1385
51.3 IPS |
|
|
Text Classification (SP)
|
100% |
307
410.3 IPS |
|
|
Text Classification (HP)
|
99% |
360
480.1 IPS |
|
|
Text Classification (Q)
|
88% |
427
575.5 IPS |
|
|
Machine Translation (SP)
|
100% |
634
10.9 IPS |
|
|
Machine Translation (HP)
|
100% |
617
10.6 IPS |
|
|
Machine Translation (Q)
|
50% |
593
21.0 IPS |
