Google Pixel 6
Geekbench ML Score
746
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 07 2024 11:31 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 12 |
| Model | Google Pixel 6 |
| Model ID | Google Pixel 6 |
| Motherboard | oriole |
| Governor | performance |
| 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 | 7.28 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
364
68.0 IPS |
|
|
Image Classification (F16)
|
100% |
367
68.7 IPS |
|
|
Image Classification (I8)
|
97% |
823
154.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
413
6.90 IPS |
|
|
Image Segmentation (F16)
|
100% |
413
6.90 IPS |
|
|
Image Segmentation (I8)
|
98% |
681
11.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
770
0.93 IPS |
|
|
Pose Estimation (F16)
|
100% |
741
0.90 IPS |
|
|
Pose Estimation (I8)
|
100% |
3583
4.34 IPS |
|
|
Object Detection (F32)
|
100% |
331
24.7 IPS |
|
|
Object Detection (F16)
|
100% |
322
24.1 IPS |
|
|
Object Detection (I8)
|
61% |
786
58.7 IPS |
|
|
Face Detection (F32)
|
100% |
731
8.69 IPS |
|
|
Face Detection (F16)
|
100% |
730
8.68 IPS |
|
|
Face Detection (I8)
|
86% |
1744
20.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
742
5.75 IPS |
|
|
Depth Estimation (F16)
|
100% |
717
5.56 IPS |
|
|
Depth Estimation (I8)
|
95% |
1853
14.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1319
1.74 IPS |
|
|
Style Transfer (F16)
|
100% |
1331
1.75 IPS |
|
|
Style Transfer (I8)
|
98% |
2926
3.85 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
551
19.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
550
19.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1912
68.3 IPS |
|
|
Text Classification (F32)
|
100% |
523
751.0 IPS |
|
|
Text Classification (F16)
|
100% |
523
751.2 IPS |
|
|
Text Classification (I8)
|
92% |
263
377.9 IPS |
|
|
Machine Translation (F32)
|
100% |
888
16.3 IPS |
|
|
Machine Translation (F16)
|
100% |
878
16.2 IPS |
|
|
Machine Translation (I8)
|
64% |
457
8.40 IPS |
