Google Pixel 7
Geekbench ML Score
488
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 15 2024 03:42 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% |
344
64.4 IPS |
|
|
Image Classification (F16)
|
100% |
339
63.5 IPS |
|
|
Image Classification (I8)
|
97% |
511
95.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
403
6.74 IPS |
|
|
Image Segmentation (F16)
|
100% |
389
6.49 IPS |
|
|
Image Segmentation (I8)
|
98% |
570
9.52 IPS |
|
|
Pose Estimation (F32)
|
100% |
665
0.81 IPS |
|
|
Pose Estimation (F16)
|
100% |
630
0.76 IPS |
|
|
Pose Estimation (I8)
|
100% |
3093
3.75 IPS |
|
|
Object Detection (F32)
|
100% |
250
18.7 IPS |
|
|
Object Detection (F16)
|
100% |
229
17.1 IPS |
|
|
Object Detection (I8)
|
61% |
394
29.4 IPS |
|
|
Face Detection (F32)
|
100% |
494
5.88 IPS |
|
|
Face Detection (F16)
|
100% |
410
4.88 IPS |
|
|
Face Detection (I8)
|
86% |
960
11.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
474
3.67 IPS |
|
|
Depth Estimation (F16)
|
100% |
403
3.12 IPS |
|
|
Depth Estimation (I8)
|
95% |
829
6.43 IPS |
|
|
Style Transfer (F32)
|
100% |
911
1.20 IPS |
|
|
Style Transfer (F16)
|
100% |
800
1.05 IPS |
|
|
Style Transfer (I8)
|
98% |
1986
2.61 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
383
13.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
380
13.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1065
38.0 IPS |
|
|
Text Classification (F32)
|
100% |
174
250.6 IPS |
|
|
Text Classification (F16)
|
100% |
175
251.1 IPS |
|
|
Text Classification (I8)
|
92% |
348
500.1 IPS |
|
|
Machine Translation (F32)
|
100% |
362
6.66 IPS |
|
|
Machine Translation (F16)
|
100% |
374
6.88 IPS |
|
|
Machine Translation (I8)
|
64% |
300
5.52 IPS |
