vivo V2417A
Geekbench ML Score
1399
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 12 2025 06:16 AM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | vivo V2417A |
| Model ID | vivo V2417A |
| 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 @ 3.40 GHz |
| Memory Information | |
|---|---|
| Size | 11.06 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
913
170.8 IPS |
|
|
Image Classification (F16)
|
100% |
899
168.3 IPS |
|
|
Image Classification (I8)
|
97% |
1517
283.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
1153
19.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
1153
19.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
1320
22.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
1438
1.74 IPS |
|
|
Pose Estimation (F16)
|
100% |
1412
1.71 IPS |
|
|
Pose Estimation (I8)
|
100% |
6192
7.50 IPS |
|
|
Object Detection (F32)
|
100% |
775
57.8 IPS |
|
|
Object Detection (F16)
|
100% |
776
57.9 IPS |
|
|
Object Detection (I8)
|
61% |
1344
100.3 IPS |
|
|
Face Detection (F32)
|
100% |
1738
20.7 IPS |
|
|
Face Detection (F16)
|
100% |
1748
20.8 IPS |
|
|
Face Detection (I8)
|
86% |
2566
30.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
1503
11.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
1511
11.7 IPS |
|
|
Depth Estimation (I8)
|
95% |
2608
20.2 IPS |
|
|
Style Transfer (F32)
|
100% |
2244
2.95 IPS |
|
|
Style Transfer (F16)
|
100% |
2158
2.84 IPS |
|
|
Style Transfer (I8)
|
98% |
4905
6.45 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
950
33.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
955
34.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2556
91.3 IPS |
|
|
Text Classification (F32)
|
100% |
850
1.22 KIPS |
|
|
Text Classification (F16)
|
100% |
787
1.13 KIPS |
|
|
Text Classification (I8)
|
92% |
573
823.6 IPS |
|
|
Machine Translation (F32)
|
100% |
1451
26.7 IPS |
|
|
Machine Translation (F16)
|
100% |
1416
26.1 IPS |
|
|
Machine Translation (I8)
|
64% |
538
9.90 IPS |
