Google Pixel 7
Geekbench ML Score
791
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 06:50 AM |
| Views | 2 |
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% |
338
63.2 IPS |
|
|
Image Classification (F16)
|
100% |
380
71.1 IPS |
|
|
Image Classification (I8)
|
97% |
732
137.1 IPS |
|
|
Image Segmentation (F32)
|
100% |
444
7.41 IPS |
|
|
Image Segmentation (F16)
|
100% |
447
7.46 IPS |
|
|
Image Segmentation (I8)
|
98% |
751
12.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
806
0.98 IPS |
|
|
Pose Estimation (F16)
|
100% |
784
0.95 IPS |
|
|
Pose Estimation (I8)
|
100% |
4297
5.20 IPS |
|
|
Object Detection (F32)
|
100% |
420
31.4 IPS |
|
|
Object Detection (F16)
|
100% |
417
31.2 IPS |
|
|
Object Detection (I8)
|
61% |
859
64.2 IPS |
|
|
Face Detection (F32)
|
100% |
788
9.37 IPS |
|
|
Face Detection (F16)
|
100% |
777
9.24 IPS |
|
|
Face Detection (I8)
|
86% |
2046
24.3 IPS |
|
|
Depth Estimation (F32)
|
100% |
778
6.04 IPS |
|
|
Depth Estimation (F16)
|
100% |
793
6.15 IPS |
|
|
Depth Estimation (I8)
|
95% |
1641
12.7 IPS |
|
|
Style Transfer (F32)
|
100% |
1423
1.87 IPS |
|
|
Style Transfer (F16)
|
100% |
1216
1.60 IPS |
|
|
Style Transfer (I8)
|
98% |
2912
3.83 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
518
18.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
541
19.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
2069
73.9 IPS |
|
|
Text Classification (F32)
|
100% |
566
814.0 IPS |
|
|
Text Classification (F16)
|
100% |
483
694.1 IPS |
|
|
Text Classification (I8)
|
92% |
540
775.5 IPS |
|
|
Machine Translation (F32)
|
100% |
839
15.4 IPS |
|
|
Machine Translation (F16)
|
100% |
856
15.8 IPS |
|
|
Machine Translation (I8)
|
64% |
398
7.33 IPS |
