Google Pixel 7
Geekbench ML Score
610
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 18 2024 03:25 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% |
329
61.6 IPS |
|
|
Image Classification (F16)
|
100% |
277
51.8 IPS |
|
|
Image Classification (I8)
|
97% |
677
126.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
411
6.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
403
6.73 IPS |
|
|
Image Segmentation (I8)
|
98% |
575
9.60 IPS |
|
|
Pose Estimation (F32)
|
100% |
691
0.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
627
0.76 IPS |
|
|
Pose Estimation (I8)
|
100% |
3383
4.10 IPS |
|
|
Object Detection (F32)
|
100% |
315
23.5 IPS |
|
|
Object Detection (F16)
|
100% |
296
22.1 IPS |
|
|
Object Detection (I8)
|
61% |
617
46.0 IPS |
|
|
Face Detection (F32)
|
100% |
663
7.88 IPS |
|
|
Face Detection (F16)
|
100% |
592
7.04 IPS |
|
|
Face Detection (I8)
|
86% |
1292
15.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
592
4.59 IPS |
|
|
Depth Estimation (F16)
|
100% |
559
4.34 IPS |
|
|
Depth Estimation (I8)
|
95% |
1146
8.89 IPS |
|
|
Style Transfer (F32)
|
100% |
1104
1.45 IPS |
|
|
Style Transfer (F16)
|
100% |
1090
1.43 IPS |
|
|
Style Transfer (I8)
|
98% |
2044
2.69 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
402
14.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
433
15.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1414
50.5 IPS |
|
|
Text Classification (F32)
|
100% |
368
529.4 IPS |
|
|
Text Classification (F16)
|
100% |
393
564.5 IPS |
|
|
Text Classification (I8)
|
92% |
345
496.2 IPS |
|
|
Machine Translation (F32)
|
100% |
632
11.6 IPS |
|
|
Machine Translation (F16)
|
100% |
681
12.5 IPS |
|
|
Machine Translation (I8)
|
64% |
307
5.66 IPS |
