Google Pixel 6
Geekbench ML Score
337
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 07 2024 11:13 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Google Pixel 6 |
| Model ID | Google Pixel 6 |
| Motherboard | oriole |
| Governor | schedutil |
| 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 | 7.42 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
311
58.2 IPS |
|
|
Image Classification (F16)
|
100% |
128
24.0 IPS |
|
|
Image Classification (I8)
|
97% |
269
50.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
269
4.50 IPS |
|
|
Image Segmentation (F16)
|
100% |
281
4.69 IPS |
|
|
Image Segmentation (I8)
|
98% |
297
4.96 IPS |
|
|
Pose Estimation (F32)
|
100% |
382
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
358
0.43 IPS |
|
|
Pose Estimation (I8)
|
100% |
1567
1.90 IPS |
|
|
Object Detection (F32)
|
100% |
101
7.51 IPS |
|
|
Object Detection (F16)
|
100% |
117
8.73 IPS |
|
|
Object Detection (I8)
|
61% |
74
5.56 IPS |
|
|
Face Detection (F32)
|
100% |
197
2.34 IPS |
|
|
Face Detection (F16)
|
100% |
277
3.29 IPS |
|
|
Face Detection (I8)
|
86% |
689
8.20 IPS |
|
|
Depth Estimation (F32)
|
100% |
356
2.76 IPS |
|
|
Depth Estimation (F16)
|
100% |
422
3.27 IPS |
|
|
Depth Estimation (I8)
|
95% |
911
7.06 IPS |
|
|
Style Transfer (F32)
|
100% |
817
1.07 IPS |
|
|
Style Transfer (F16)
|
100% |
760
1.00 IPS |
|
|
Style Transfer (I8)
|
98% |
1836
2.41 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
255
9.12 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
257
9.19 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
832
29.7 IPS |
|
|
Text Classification (F32)
|
100% |
191
274.4 IPS |
|
|
Text Classification (F16)
|
100% |
191
273.9 IPS |
|
|
Text Classification (I8)
|
92% |
240
344.7 IPS |
|
|
Machine Translation (F32)
|
100% |
420
7.72 IPS |
|
|
Machine Translation (F16)
|
100% |
412
7.57 IPS |
|
|
Machine Translation (I8)
|
64% |
312
5.75 IPS |
