vivo VPR2401A
Geekbench ML Score
1063
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | December 10 2025 02:18 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | vivo VPR2401A |
| Model ID | vivo VPR2401A |
| Motherboard | anorak |
| Governor | walt |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3403 revision 2 |
| Base Frequency | 2.36 GHz |
| Cluster 1 | 6 Cores @ 2.36 GHz |
| Memory Information | |
|---|---|
| Size | 15.33 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
772
144.4 IPS |
|
|
Image Classification (F16)
|
100% |
1284
240.3 IPS |
|
|
Image Classification (I8)
|
99% |
1192
223.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
927
15.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
1627
27.2 IPS |
|
|
Image Segmentation (I8)
|
98% |
1582
26.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
821
0.99 IPS |
|
|
Pose Estimation (F16)
|
100% |
1485
1.80 IPS |
|
|
Pose Estimation (I8)
|
100% |
1490
1.80 IPS |
|
|
Object Detection (F32)
|
100% |
530
39.6 IPS |
|
|
Object Detection (F16)
|
100% |
535
40.0 IPS |
|
|
Object Detection (I8)
|
62% |
557
41.6 IPS |
|
|
Face Detection (F32)
|
100% |
2534
30.1 IPS |
|
|
Face Detection (F16)
|
97% |
4218
50.2 IPS |
|
|
Face Detection (I8)
|
86% |
3676
43.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
1667
12.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
3253
25.2 IPS |
|
|
Depth Estimation (I8)
|
95% |
3212
24.9 IPS |
|
|
Style Transfer (F32)
|
100% |
5172
6.80 IPS |
|
|
Style Transfer (F16)
|
100% |
9367
12.3 IPS |
|
|
Style Transfer (I8)
|
98% |
7332
9.65 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
488
17.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
421
15.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
416
14.9 IPS |
|
|
Text Classification (F32)
|
100% |
171
245.8 IPS |
|
|
Text Classification (F16)
|
100% |
173
248.2 IPS |
|
|
Text Classification (I8)
|
92% |
315
453.3 IPS |
|
|
Machine Translation (F32)
|
100% |
318
5.86 IPS |
|
|
Machine Translation (F16)
|
100% |
318
5.84 IPS |
|
|
Machine Translation (I8)
|
64% |
398
7.33 IPS |
