Google Pixel 4
Geekbench ML Score
175
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 04:31 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Google Pixel 4 |
| Model ID | Google Pixel 4 |
| Motherboard | flame |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | Qualcomm Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 81 architecture 8 variant 13 part 2052 revision 14 |
| Base Frequency | 1.78 GHz |
| Cluster 1 | 4 Cores @ 1.79 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 5.34 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
72
13.5 IPS |
|
|
Image Classification (F16)
|
100% |
72
13.5 IPS |
|
|
Image Classification (I8)
|
97% |
79
14.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
237
3.95 IPS |
|
|
Image Segmentation (F16)
|
100% |
234
3.91 IPS |
|
|
Image Segmentation (I8)
|
98% |
245
4.10 IPS |
|
|
Pose Estimation (F32)
|
100% |
511
0.62 IPS |
|
|
Pose Estimation (F16)
|
100% |
498
0.60 IPS |
|
|
Pose Estimation (I8)
|
100% |
1807
2.19 IPS |
|
|
Object Detection (F32)
|
100% |
107
8.01 IPS |
|
|
Object Detection (F16)
|
100% |
107
8.01 IPS |
|
|
Object Detection (I8)
|
61% |
128
9.53 IPS |
|
|
Face Detection (F32)
|
100% |
320
3.80 IPS |
|
|
Face Detection (F16)
|
100% |
321
3.82 IPS |
|
|
Face Detection (I8)
|
86% |
422
5.02 IPS |
|
|
Depth Estimation (F32)
|
100% |
317
2.46 IPS |
|
|
Depth Estimation (F16)
|
100% |
317
2.46 IPS |
|
|
Depth Estimation (I8)
|
95% |
435
3.37 IPS |
|
|
Style Transfer (F32)
|
100% |
911
1.20 IPS |
|
|
Style Transfer (F16)
|
100% |
899
1.18 IPS |
|
|
Style Transfer (I8)
|
98% |
2379
3.13 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
168
6.00 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
172
6.14 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
264
9.44 IPS |
|
|
Text Classification (F32)
|
100% |
15
20.9 IPS |
|
|
Text Classification (F16)
|
100% |
15
20.9 IPS |
|
|
Text Classification (I8)
|
92% |
16
22.6 IPS |
|
|
Machine Translation (F32)
|
100% |
38
0.69 IPS |
|
|
Machine Translation (F16)
|
100% |
38
0.70 IPS |
|
|
Machine Translation (I8)
|
64% |
36
0.67 IPS |
