Google Pixel Fold
Geekbench ML Score
788
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | navtiidia |
| Upload Date | August 01 2024 08:37 PM |
| Views | 4 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Google Pixel Fold |
| Model ID | Google Pixel Fold |
| Motherboard | felix |
| Governor | sched_pixel |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 2 Cores @ 2.35 GHz |
| Cluster 3 | 2 Cores @ 2.85 GHz |
| Memory Information | |
|---|---|
| Size | 11.20 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
373
69.9 IPS |
|
|
Image Classification (F16)
|
100% |
382
71.5 IPS |
|
|
Image Classification (I8)
|
97% |
761
142.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
459
7.67 IPS |
|
|
Image Segmentation (F16)
|
100% |
460
7.69 IPS |
|
|
Image Segmentation (I8)
|
98% |
743
12.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
817
0.99 IPS |
|
|
Pose Estimation (F16)
|
100% |
789
0.95 IPS |
|
|
Pose Estimation (I8)
|
100% |
4007
4.85 IPS |
|
|
Object Detection (F32)
|
100% |
388
29.0 IPS |
|
|
Object Detection (F16)
|
100% |
394
29.4 IPS |
|
|
Object Detection (I8)
|
61% |
862
64.4 IPS |
|
|
Face Detection (F32)
|
100% |
728
8.66 IPS |
|
|
Face Detection (F16)
|
100% |
735
8.74 IPS |
|
|
Face Detection (I8)
|
86% |
1692
20.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
712
5.52 IPS |
|
|
Depth Estimation (F16)
|
100% |
660
5.12 IPS |
|
|
Depth Estimation (I8)
|
95% |
1470
11.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1315
1.73 IPS |
|
|
Style Transfer (F16)
|
100% |
1489
1.96 IPS |
|
|
Style Transfer (I8)
|
98% |
3080
4.05 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
571
20.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
569
20.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2194
78.4 IPS |
|
|
Text Classification (F32)
|
100% |
525
755.2 IPS |
|
|
Text Classification (F16)
|
100% |
547
785.5 IPS |
|
|
Text Classification (I8)
|
92% |
547
786.2 IPS |
|
|
Machine Translation (F32)
|
100% |
907
16.7 IPS |
|
|
Machine Translation (F16)
|
100% |
885
16.3 IPS |
|
|
Machine Translation (I8)
|
64% |
407
7.48 IPS |
