Google Pixel 6
Geekbench ML Score
698
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 21 2024 09:35 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Google Pixel 6 |
| Model ID | Google Pixel 6 |
| Motherboard | oriole |
| 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 @ 2.25 GHz |
| Cluster 3 | 2 Cores @ 2.80 GHz |
| Memory Information | |
|---|---|
| Size | 7.44 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
317
59.3 IPS |
|
|
Image Classification (F16)
|
100% |
297
55.6 IPS |
|
|
Image Classification (I8)
|
97% |
678
126.9 IPS |
|
|
Image Segmentation (F32)
|
100% |
408
6.81 IPS |
|
|
Image Segmentation (F16)
|
100% |
390
6.52 IPS |
|
|
Image Segmentation (I8)
|
98% |
677
11.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
705
0.85 IPS |
|
|
Pose Estimation (F16)
|
100% |
679
0.82 IPS |
|
|
Pose Estimation (I8)
|
100% |
3751
4.54 IPS |
|
|
Object Detection (F32)
|
100% |
310
23.2 IPS |
|
|
Object Detection (F16)
|
100% |
332
24.8 IPS |
|
|
Object Detection (I8)
|
61% |
791
59.1 IPS |
|
|
Face Detection (F32)
|
100% |
705
8.38 IPS |
|
|
Face Detection (F16)
|
100% |
704
8.37 IPS |
|
|
Face Detection (I8)
|
86% |
1682
20.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
682
5.29 IPS |
|
|
Depth Estimation (F16)
|
100% |
647
5.02 IPS |
|
|
Depth Estimation (I8)
|
95% |
1620
12.6 IPS |
|
|
Style Transfer (F32)
|
100% |
1221
1.61 IPS |
|
|
Style Transfer (F16)
|
100% |
1210
1.59 IPS |
|
|
Style Transfer (I8)
|
98% |
2892
3.80 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
456
16.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
478
17.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1737
62.0 IPS |
|
|
Text Classification (F32)
|
100% |
501
720.6 IPS |
|
|
Text Classification (F16)
|
100% |
473
680.1 IPS |
|
|
Text Classification (I8)
|
92% |
495
711.7 IPS |
|
|
Machine Translation (F32)
|
100% |
711
13.1 IPS |
|
|
Machine Translation (F16)
|
100% |
682
12.5 IPS |
|
|
Machine Translation (I8)
|
64% |
384
7.07 IPS |
