Vivo X90
Geekbench ML Score
610
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 18 2024 03:43 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Vivo X90 |
| Model ID | vivo V2241A |
| Motherboard | k6985v1_64 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.85 GHz |
| Cluster 3 | 1 Core @ 3.05 GHz |
| Memory Information | |
|---|---|
| Size | 7.16 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
84
15.6 IPS |
|
|
Image Classification (F16)
|
100% |
219
41.0 IPS |
|
|
Image Classification (I8)
|
97% |
346
64.7 IPS |
|
|
Image Segmentation (F32)
|
100% |
520
8.68 IPS |
|
|
Image Segmentation (F16)
|
100% |
424
7.08 IPS |
|
|
Image Segmentation (I8)
|
98% |
529
8.83 IPS |
|
|
Pose Estimation (F32)
|
100% |
943
1.14 IPS |
|
|
Pose Estimation (F16)
|
100% |
1012
1.23 IPS |
|
|
Pose Estimation (I8)
|
100% |
3992
4.83 IPS |
|
|
Object Detection (F32)
|
100% |
333
24.8 IPS |
|
|
Object Detection (F16)
|
100% |
323
24.1 IPS |
|
|
Object Detection (I8)
|
61% |
465
34.7 IPS |
|
|
Face Detection (F32)
|
100% |
865
10.3 IPS |
|
|
Face Detection (F16)
|
100% |
825
9.81 IPS |
|
|
Face Detection (I8)
|
86% |
975
11.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
811
6.29 IPS |
|
|
Depth Estimation (F16)
|
100% |
793
6.15 IPS |
|
|
Depth Estimation (I8)
|
95% |
1284
9.96 IPS |
|
|
Style Transfer (F32)
|
100% |
1730
2.28 IPS |
|
|
Style Transfer (F16)
|
100% |
1623
2.13 IPS |
|
|
Style Transfer (I8)
|
98% |
3039
4.00 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
437
15.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
470
16.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
759
27.1 IPS |
|
|
Text Classification (F32)
|
100% |
412
592.1 IPS |
|
|
Text Classification (F16)
|
100% |
359
516.4 IPS |
|
|
Text Classification (I8)
|
92% |
203
291.7 IPS |
|
|
Machine Translation (F32)
|
100% |
617
11.4 IPS |
|
|
Machine Translation (F16)
|
100% |
509
9.37 IPS |
|
|
Machine Translation (I8)
|
64% |
363
6.68 IPS |
