Google Pixel 8
Geekbench ML Score
799
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 24 2024 12:02 AM |
| 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% |
372
69.5 IPS |
|
|
Image Classification (F16)
|
100% |
467
87.3 IPS |
|
|
Image Classification (I8)
|
97% |
813
152.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
573
9.57 IPS |
|
|
Image Segmentation (F16)
|
100% |
573
9.57 IPS |
|
|
Image Segmentation (I8)
|
98% |
706
11.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
845
1.02 IPS |
|
|
Pose Estimation (F16)
|
100% |
822
1.00 IPS |
|
|
Pose Estimation (I8)
|
100% |
4252
5.15 IPS |
|
|
Object Detection (F32)
|
100% |
454
33.9 IPS |
|
|
Object Detection (F16)
|
100% |
458
34.2 IPS |
|
|
Object Detection (I8)
|
61% |
872
65.1 IPS |
|
|
Face Detection (F32)
|
100% |
887
10.5 IPS |
|
|
Face Detection (F16)
|
100% |
610
7.26 IPS |
|
|
Face Detection (I8)
|
86% |
1270
15.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
836
6.48 IPS |
|
|
Depth Estimation (F16)
|
100% |
854
6.62 IPS |
|
|
Depth Estimation (I8)
|
95% |
1404
10.9 IPS |
|
|
Style Transfer (F32)
|
100% |
1586
2.09 IPS |
|
|
Style Transfer (F16)
|
100% |
1587
2.09 IPS |
|
|
Style Transfer (I8)
|
98% |
2994
3.94 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
567
20.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
563
20.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1738
62.1 IPS |
|
|
Text Classification (F32)
|
100% |
462
664.0 IPS |
|
|
Text Classification (F16)
|
100% |
446
641.4 IPS |
|
|
Text Classification (I8)
|
92% |
421
604.6 IPS |
|
|
Machine Translation (F32)
|
100% |
864
15.9 IPS |
|
|
Machine Translation (F16)
|
100% |
855
15.7 IPS |
|
|
Machine Translation (I8)
|
64% |
378
6.95 IPS |
