Google Pixel 8
Geekbench ML Score
926
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 22 2024 02:43 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Google Pixel 8 |
| Model ID | Google Pixel 8 |
| Motherboard | shiba |
| Governor | sched_pixel |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 9 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 1.70 GHz |
| Cluster 1 | 4 Cores @ 1.70 GHz |
| Cluster 2 | 4 Cores @ 2.37 GHz |
| Cluster 3 | 1 Core @ 2.91 GHz |
| Memory Information | |
|---|---|
| Size | 7.42 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
483
90.3 IPS |
|
|
Image Classification (F16)
|
100% |
490
91.6 IPS |
|
|
Image Classification (I8)
|
97% |
836
156.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
588
9.82 IPS |
|
|
Image Segmentation (F16)
|
100% |
594
9.91 IPS |
|
|
Image Segmentation (I8)
|
98% |
732
12.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
930
1.13 IPS |
|
|
Pose Estimation (F16)
|
100% |
1012
1.23 IPS |
|
|
Pose Estimation (I8)
|
100% |
4782
5.79 IPS |
|
|
Object Detection (F32)
|
100% |
552
41.2 IPS |
|
|
Object Detection (F16)
|
100% |
511
38.1 IPS |
|
|
Object Detection (I8)
|
61% |
1015
75.8 IPS |
|
|
Face Detection (F32)
|
100% |
1081
12.9 IPS |
|
|
Face Detection (F16)
|
100% |
1052
12.5 IPS |
|
|
Face Detection (I8)
|
86% |
1498
17.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
982
7.61 IPS |
|
|
Depth Estimation (F16)
|
100% |
919
7.12 IPS |
|
|
Depth Estimation (I8)
|
95% |
1731
13.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1624
2.14 IPS |
|
|
Style Transfer (F16)
|
100% |
1665
2.19 IPS |
|
|
Style Transfer (I8)
|
98% |
3597
4.73 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
689
24.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
704
25.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2259
80.7 IPS |
|
|
Text Classification (F32)
|
100% |
557
800.9 IPS |
|
|
Text Classification (F16)
|
100% |
528
758.8 IPS |
|
|
Text Classification (I8)
|
92% |
525
754.6 IPS |
|
|
Machine Translation (F32)
|
100% |
979
18.0 IPS |
|
|
Machine Translation (F16)
|
100% |
975
17.9 IPS |
|
|
Machine Translation (I8)
|
64% |
366
6.73 IPS |
