vivo V2464A
Geekbench AI Score
247
Single Precision Score
248
Half Precision Score
592
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| User | 46fy45 |
| Upload Date | January 27 2026 05:40 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | vivo V2464A |
| Model ID | vivo V2464A |
| Motherboard | sun |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3457 revision 1 |
| Base Frequency | 1.84 GHz |
| Cluster 1 | 3 Cores @ 1.84 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Cluster 3 | 1 Core @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 11.01 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
147
27.3 IPS |
|
|
Image Classification (HP)
|
100% |
148
27.5 IPS |
|
|
Image Classification (Q)
|
99% |
390
72.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
198
3.21 IPS |
|
|
Image Segmentation (HP)
|
100% |
201
3.25 IPS |
|
|
Image Segmentation (Q)
|
98% |
425
6.92 IPS |
|
|
Pose Estimation (SP)
|
100% |
253
0.30 IPS |
|
|
Pose Estimation (HP)
|
100% |
255
0.30 IPS |
|
|
Pose Estimation (Q)
|
98% |
954
1.12 IPS |
|
|
Object Detection (SP)
|
100% |
142
11.2 IPS |
|
|
Object Detection (HP)
|
100% |
143
11.3 IPS |
|
|
Object Detection (Q)
|
87% |
420
33.7 IPS |
|
|
Face Detection (SP)
|
100% |
402
4.77 IPS |
|
|
Face Detection (HP)
|
100% |
406
4.82 IPS |
|
|
Face Detection (Q)
|
97% |
895
10.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
328
2.53 IPS |
|
|
Depth Estimation (HP)
|
99% |
328
2.53 IPS |
|
|
Depth Estimation (Q)
|
64% |
796
7.22 IPS |
|
|
Style Transfer (SP)
|
100% |
548
0.70 IPS |
|
|
Style Transfer (HP)
|
100% |
546
0.70 IPS |
|
|
Style Transfer (Q)
|
98% |
1667
2.15 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
160
5.92 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
160
5.92 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
583
21.6 IPS |
|
|
Text Classification (SP)
|
100% |
202
269.9 IPS |
|
|
Text Classification (HP)
|
100% |
204
271.8 IPS |
|
|
Text Classification (Q)
|
91% |
379
509.1 IPS |
|
|
Machine Translation (SP)
|
100% |
354
6.09 IPS |
|
|
Machine Translation (HP)
|
100% |
354
6.11 IPS |
|
|
Machine Translation (Q)
|
57% |
307
7.51 IPS |
