vivo I1927
Geekbench ML Score
479
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 17 2024 05:59 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | vivo I1927 |
| Model ID | vivo I1927 |
| Motherboard | kona |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
365
68.3 IPS |
|
|
Image Classification (F16)
|
100% |
566
106.0 IPS |
|
|
Image Classification (I8)
|
97% |
1165
218.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
427
7.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
540
9.01 IPS |
|
|
Image Segmentation (I8)
|
98% |
1090
18.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
1352
1.64 IPS |
|
|
Pose Estimation (F16)
|
100% |
5090
6.16 IPS |
|
|
Pose Estimation (I8)
|
100% |
10826
13.1 IPS |
|
|
Object Detection (F32)
|
100% |
305
22.7 IPS |
|
|
Object Detection (F16)
|
99% |
446
33.3 IPS |
|
|
Object Detection (I8)
|
59% |
588
43.9 IPS |
|
|
Face Detection (F32)
|
100% |
878
10.4 IPS |
|
|
Face Detection (F16)
|
97% |
1059
12.6 IPS |
|
|
Face Detection (I8)
|
88% |
3291
39.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
440
3.41 IPS |
|
|
Depth Estimation (F16)
|
100% |
531
4.11 IPS |
|
|
Depth Estimation (I8)
|
82% |
6928
53.7 IPS |
|
|
Style Transfer (F32)
|
100% |
745
0.98 IPS |
|
|
Style Transfer (F16)
|
100% |
795
1.05 IPS |
|
|
Style Transfer (I8)
|
98% |
3582
4.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
701
25.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1513
54.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
4851
173.2 IPS |
|
|
Text Classification (F32)
|
64% |
3
4.35 IPS |
|
|
Text Classification (F16)
|
64% |
3
4.22 IPS |
|
|
Text Classification (I8)
|
92% |
62
89.8 IPS |
|
|
Machine Translation (F32)
|
100% |
69
1.27 IPS |
|
|
Machine Translation (F16)
|
100% |
354
6.52 IPS |
|
|
Machine Translation (I8)
|
0
|
