Google Pixel 7
Geekbench ML Score
696
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 23 2024 10:39 PM |
| Views | 5 |
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% |
355
66.4 IPS |
|
|
Image Classification (F16)
|
100% |
337
63.2 IPS |
|
|
Image Classification (I8)
|
97% |
685
128.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
450
7.51 IPS |
|
|
Image Segmentation (F16)
|
100% |
431
7.20 IPS |
|
|
Image Segmentation (I8)
|
98% |
738
12.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
743
0.90 IPS |
|
|
Pose Estimation (F16)
|
100% |
697
0.84 IPS |
|
|
Pose Estimation (I8)
|
100% |
3418
4.14 IPS |
|
|
Object Detection (F32)
|
100% |
318
23.7 IPS |
|
|
Object Detection (F16)
|
100% |
286
21.3 IPS |
|
|
Object Detection (I8)
|
61% |
727
54.3 IPS |
|
|
Face Detection (F32)
|
100% |
642
7.64 IPS |
|
|
Face Detection (F16)
|
100% |
652
7.76 IPS |
|
|
Face Detection (I8)
|
86% |
1714
20.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
613
4.75 IPS |
|
|
Depth Estimation (F16)
|
100% |
602
4.67 IPS |
|
|
Depth Estimation (I8)
|
95% |
1643
12.7 IPS |
|
|
Style Transfer (F32)
|
100% |
1093
1.44 IPS |
|
|
Style Transfer (F16)
|
100% |
1082
1.42 IPS |
|
|
Style Transfer (I8)
|
98% |
2820
3.71 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
464
16.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
430
15.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1976
70.6 IPS |
|
|
Text Classification (F32)
|
100% |
498
715.1 IPS |
|
|
Text Classification (F16)
|
100% |
525
754.2 IPS |
|
|
Text Classification (I8)
|
92% |
436
626.3 IPS |
|
|
Machine Translation (F32)
|
100% |
794
14.6 IPS |
|
|
Machine Translation (F16)
|
100% |
736
13.5 IPS |
|
|
Machine Translation (I8)
|
64% |
375
6.90 IPS |
