Google Pixel 7
Geekbench ML Score
718
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 25 2024 10:50 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Google Pixel 7 |
| Model ID | Google Pixel 7 |
| Motherboard | panther |
| 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 | 7.30 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
373
69.7 IPS |
|
|
Image Classification (F16)
|
100% |
355
66.5 IPS |
|
|
Image Classification (I8)
|
97% |
597
111.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
428
7.14 IPS |
|
|
Image Segmentation (F16)
|
100% |
423
7.07 IPS |
|
|
Image Segmentation (I8)
|
98% |
734
12.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
667
0.81 IPS |
|
|
Pose Estimation (F16)
|
100% |
646
0.78 IPS |
|
|
Pose Estimation (I8)
|
100% |
3893
4.71 IPS |
|
|
Object Detection (F32)
|
100% |
290
21.6 IPS |
|
|
Object Detection (F16)
|
100% |
288
21.5 IPS |
|
|
Object Detection (I8)
|
61% |
693
51.7 IPS |
|
|
Face Detection (F32)
|
100% |
714
8.48 IPS |
|
|
Face Detection (F16)
|
100% |
727
8.64 IPS |
|
|
Face Detection (I8)
|
86% |
1914
22.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
697
5.40 IPS |
|
|
Depth Estimation (F16)
|
100% |
679
5.26 IPS |
|
|
Depth Estimation (I8)
|
95% |
1757
13.6 IPS |
|
|
Style Transfer (F32)
|
100% |
1237
1.63 IPS |
|
|
Style Transfer (F16)
|
100% |
1212
1.59 IPS |
|
|
Style Transfer (I8)
|
98% |
2831
3.72 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
512
18.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
509
18.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2138
76.3 IPS |
|
|
Text Classification (F32)
|
100% |
471
677.5 IPS |
|
|
Text Classification (F16)
|
100% |
438
629.1 IPS |
|
|
Text Classification (I8)
|
92% |
487
700.1 IPS |
|
|
Machine Translation (F32)
|
100% |
754
13.9 IPS |
|
|
Machine Translation (F16)
|
100% |
776
14.3 IPS |
|
|
Machine Translation (I8)
|
64% |
428
7.88 IPS |
