vivo V2247
Geekbench AI Score
306
Single Precision Score
308
Half Precision Score
365
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | April 23 2025 04:47 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo V2247 |
| Model ID | vivo V2247 |
| Motherboard | bengal |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3337 revision 0 |
| Base Frequency | 1.90 GHz |
| Cluster 1 | 4 Cores @ 1.90 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.43 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
161
30.0 IPS |
|
|
Image Classification (HP)
|
100% |
161
29.9 IPS |
|
|
Image Classification (Q)
|
100% |
291
54.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
200
3.24 IPS |
|
|
Image Segmentation (HP)
|
100% |
202
3.28 IPS |
|
|
Image Segmentation (Q)
|
98% |
368
5.99 IPS |
|
|
Pose Estimation (SP)
|
100% |
705
0.82 IPS |
|
|
Pose Estimation (HP)
|
100% |
772
0.90 IPS |
|
|
Pose Estimation (Q)
|
84% |
593
0.70 IPS |
|
|
Object Detection (SP)
|
100% |
155
12.3 IPS |
|
|
Object Detection (HP)
|
100% |
129
10.2 IPS |
|
|
Object Detection (Q)
|
83% |
233
18.8 IPS |
|
|
Face Detection (SP)
|
100% |
398
4.72 IPS |
|
|
Face Detection (HP)
|
100% |
453
5.39 IPS |
|
|
Face Detection (Q)
|
95% |
566
6.76 IPS |
|
|
Depth Estimation (SP)
|
100% |
541
4.17 IPS |
|
|
Depth Estimation (HP)
|
99% |
554
4.27 IPS |
|
|
Depth Estimation (Q)
|
64% |
680
6.23 IPS |
|
|
Style Transfer (SP)
|
89% |
1325
1.72 IPS |
|
|
Style Transfer (HP)
|
89% |
1333
1.73 IPS |
|
|
Style Transfer (Q)
|
98% |
1718
2.21 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
336
12.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
337
12.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
383
14.2 IPS |
|
|
Text Classification (SP)
|
100% |
114
152.3 IPS |
|
|
Text Classification (HP)
|
100% |
112
150.1 IPS |
|
|
Text Classification (Q)
|
88% |
129
173.8 IPS |
|
|
Machine Translation (SP)
|
100% |
191
3.30 IPS |
|
|
Machine Translation (HP)
|
100% |
191
3.29 IPS |
|
|
Machine Translation (Q)
|
50% |
89
3.15 IPS |
