Google Pixel 4
Geekbench ML Score
439
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 28 2024 04:08 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
208
38.9 IPS |
|
|
Image Classification (F16)
|
100% |
359
67.1 IPS |
|
|
Image Classification (I8)
|
97% |
374
70.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
275
4.59 IPS |
|
|
Image Segmentation (F16)
|
100% |
522
8.72 IPS |
|
|
Image Segmentation (I8)
|
98% |
533
8.90 IPS |
|
|
Pose Estimation (F32)
|
100% |
417
0.50 IPS |
|
|
Pose Estimation (F16)
|
100% |
309
0.37 IPS |
|
|
Pose Estimation (I8)
|
100% |
311
0.38 IPS |
|
|
Object Detection (F32)
|
100% |
191
14.2 IPS |
|
|
Object Detection (F16)
|
100% |
244
18.2 IPS |
|
|
Object Detection (I8)
|
62% |
208
15.5 IPS |
|
|
Face Detection (F32)
|
100% |
508
6.04 IPS |
|
|
Face Detection (F16)
|
97% |
1076
12.8 IPS |
|
|
Face Detection (I8)
|
87% |
1175
14.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
464
3.60 IPS |
|
|
Depth Estimation (F16)
|
100% |
923
7.16 IPS |
|
|
Depth Estimation (I8)
|
95% |
929
7.20 IPS |
|
|
Style Transfer (F32)
|
100% |
931
1.23 IPS |
|
|
Style Transfer (F16)
|
100% |
2257
2.97 IPS |
|
|
Style Transfer (I8)
|
98% |
2255
2.97 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
239
8.53 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
450
16.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
446
15.9 IPS |
|
|
Text Classification (F32)
|
100% |
196
282.2 IPS |
|
|
Text Classification (F16)
|
100% |
196
281.1 IPS |
|
|
Text Classification (I8)
|
92% |
270
388.3 IPS |
|
|
Machine Translation (F32)
|
100% |
340
6.26 IPS |
|
|
Machine Translation (F16)
|
100% |
345
6.35 IPS |
|
|
Machine Translation (I8)
|
64% |
335
6.16 IPS |
