vivo V2309
Geekbench AI Score
2153
Single Precision Score
2126
Half Precision Score
3112
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | Helltak |
| Upload Date | January 09 2025 09:20 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | vivo V2309 |
| Model ID | vivo V2309 |
| Motherboard | k6989v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.25 GHz |
| Memory Information | |
|---|---|
| Size | 14.97 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1647
306.3 IPS |
|
|
Image Classification (HP)
|
100% |
1659
308.4 IPS |
|
|
Image Classification (Q)
|
100% |
2552
474.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
2075
33.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
2048
33.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
2717
44.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
3112
3.63 IPS |
|
|
Pose Estimation (HP)
|
100% |
2982
3.48 IPS |
|
|
Pose Estimation (Q)
|
84% |
5926
7.03 IPS |
|
|
Object Detection (SP)
|
98% |
1402
111.6 IPS |
|
|
Object Detection (HP)
|
98% |
1433
114.0 IPS |
|
|
Object Detection (Q)
|
83% |
2073
167.4 IPS |
|
|
Face Detection (SP)
|
100% |
3128
37.2 IPS |
|
|
Face Detection (HP)
|
100% |
3113
37.0 IPS |
|
|
Face Detection (Q)
|
95% |
4986
59.5 IPS |
|
|
Depth Estimation (SP)
|
99% |
3514
27.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
3485
26.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
5106
46.8 IPS |
|
|
Style Transfer (SP)
|
89% |
7102
9.22 IPS |
|
|
Style Transfer (HP)
|
89% |
6915
8.98 IPS |
|
|
Style Transfer (Q)
|
98% |
12990
16.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1548
57.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
1552
57.3 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3328
123.3 IPS |
|
|
Text Classification (SP)
|
100% |
735
981.0 IPS |
|
|
Text Classification (HP)
|
99% |
731
975.8 IPS |
|
|
Text Classification (Q)
|
88% |
1257
1.69 KIPS |
|
|
Machine Translation (SP)
|
100% |
1616
27.8 IPS |
|
|
Machine Translation (HP)
|
100% |
1533
26.4 IPS |
|
|
Machine Translation (Q)
|
50% |
724
25.7 IPS |
