Google Pixel 8
Geekbench ML Score
764
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 15 2024 02:26 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% |
337
63.1 IPS |
|
|
Image Classification (F16)
|
100% |
431
80.6 IPS |
|
|
Image Classification (I8)
|
97% |
745
139.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
544
9.08 IPS |
|
|
Image Segmentation (F16)
|
100% |
573
9.57 IPS |
|
|
Image Segmentation (I8)
|
98% |
735
12.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
967
1.17 IPS |
|
|
Pose Estimation (F16)
|
100% |
876
1.06 IPS |
|
|
Pose Estimation (I8)
|
100% |
3736
4.52 IPS |
|
|
Object Detection (F32)
|
100% |
373
27.8 IPS |
|
|
Object Detection (F16)
|
100% |
365
27.3 IPS |
|
|
Object Detection (I8)
|
61% |
657
49.1 IPS |
|
|
Face Detection (F32)
|
100% |
837
9.96 IPS |
|
|
Face Detection (F16)
|
100% |
839
9.98 IPS |
|
|
Face Detection (I8)
|
86% |
1435
17.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
868
6.73 IPS |
|
|
Depth Estimation (F16)
|
100% |
851
6.60 IPS |
|
|
Depth Estimation (I8)
|
95% |
1475
11.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1602
2.11 IPS |
|
|
Style Transfer (F16)
|
100% |
1637
2.15 IPS |
|
|
Style Transfer (I8)
|
98% |
3008
3.96 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
502
17.9 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
554
19.8 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1712
61.1 IPS |
|
|
Text Classification (F32)
|
100% |
413
593.4 IPS |
|
|
Text Classification (F16)
|
100% |
441
634.4 IPS |
|
|
Text Classification (I8)
|
92% |
372
535.1 IPS |
|
|
Machine Translation (F32)
|
100% |
710
13.1 IPS |
|
|
Machine Translation (F16)
|
100% |
692
12.7 IPS |
|
|
Machine Translation (I8)
|
64% |
328
6.03 IPS |
