vivo I1927
Geekbench ML Score
518
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 17 2024 06:08 PM |
| Views | 3 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
249
46.6 IPS |
|
|
Image Classification (F16)
|
100% |
357
66.8 IPS |
|
|
Image Classification (I8)
|
97% |
359
67.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
316
5.28 IPS |
|
|
Image Segmentation (F16)
|
100% |
639
10.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
622
10.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
473
0.57 IPS |
|
|
Pose Estimation (F16)
|
100% |
942
1.14 IPS |
|
|
Pose Estimation (I8)
|
100% |
940
1.14 IPS |
|
|
Object Detection (F32)
|
100% |
185
13.8 IPS |
|
|
Object Detection (F16)
|
100% |
205
15.3 IPS |
|
|
Object Detection (I8)
|
62% |
209
15.6 IPS |
|
|
Face Detection (F32)
|
100% |
584
6.94 IPS |
|
|
Face Detection (F16)
|
97% |
1107
13.2 IPS |
|
|
Face Detection (I8)
|
87% |
1147
13.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
573
4.44 IPS |
|
|
Depth Estimation (F16)
|
100% |
1083
8.40 IPS |
|
|
Depth Estimation (I8)
|
95% |
1088
8.43 IPS |
|
|
Style Transfer (F32)
|
100% |
1079
1.42 IPS |
|
|
Style Transfer (F16)
|
100% |
2633
3.46 IPS |
|
|
Style Transfer (I8)
|
98% |
2629
3.46 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
267
9.53 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
645
23.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
443
15.8 IPS |
|
|
Text Classification (F32)
|
100% |
210
302.2 IPS |
|
|
Text Classification (F16)
|
100% |
209
300.2 IPS |
|
|
Text Classification (I8)
|
92% |
362
519.8 IPS |
|
|
Machine Translation (F32)
|
100% |
349
6.43 IPS |
|
|
Machine Translation (F16)
|
100% |
353
6.50 IPS |
|
|
Machine Translation (I8)
|
64% |
383
7.06 IPS |
