vivo V2417A
Geekbench ML Score
3360
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 12 2025 06:13 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 | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
947
177.3 IPS |
|
|
Image Classification (F16)
|
100% |
4479
838.2 IPS |
|
|
Image Classification (I8)
|
97% |
9114
1.71 KIPS |
|
|
Image Segmentation (F32)
|
100% |
650
10.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
4165
69.6 IPS |
|
|
Image Segmentation (I8)
|
98% |
1785
29.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
8478
10.3 IPS |
|
|
Pose Estimation (F16)
|
100% |
17552
21.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
66047
80.0 IPS |
|
|
Object Detection (F32)
|
100% |
695
51.9 IPS |
|
|
Object Detection (F16)
|
100% |
2947
220.0 IPS |
|
|
Object Detection (I8)
|
64% |
3324
248.2 IPS |
|
|
Face Detection (F32)
|
100% |
3342
39.7 IPS |
|
|
Face Detection (F16)
|
97% |
12176
144.8 IPS |
|
|
Face Detection (I8)
|
86% |
11328
134.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
923
7.15 IPS |
|
|
Depth Estimation (F16)
|
100% |
12896
100.0 IPS |
|
|
Depth Estimation (I8)
|
95% |
30603
237.3 IPS |
|
|
Style Transfer (F32)
|
100% |
2539
3.34 IPS |
|
|
Style Transfer (F16)
|
100% |
2401
3.16 IPS |
|
|
Style Transfer (I8)
|
31% |
4674
6.15 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2111
75.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10662
380.8 IPS |
|
|
Image Super-Resolution (I8)
|
33% |
30876
1.10 KIPS |
|
|
Text Classification (F32)
|
100% |
101
144.5 IPS |
|
|
Text Classification (F16)
|
100% |
2018
2.90 KIPS |
|
|
Text Classification (I8)
|
76% |
1657
2.38 KIPS |
|
|
Machine Translation (F32)
|
100% |
368
6.78 IPS |
|
|
Machine Translation (F16)
|
100% |
2183
40.2 IPS |
|
|
Machine Translation (I8)
|
76% |
549
10.1 IPS |
