Google Pixel 7
Geekbench ML Score
573
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 19 2024 04:45 AM |
| Views | 3 |
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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
247
46.2 IPS |
|
|
Image Classification (F16)
|
100% |
245
45.9 IPS |
|
|
Image Classification (I8)
|
97% |
242
45.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
627
10.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
794
13.3 IPS |
|
|
Image Segmentation (I8)
|
98% |
755
12.6 IPS |
|
|
Pose Estimation (F32)
|
100% |
438
0.53 IPS |
|
|
Pose Estimation (F16)
|
100% |
606
0.73 IPS |
|
|
Pose Estimation (I8)
|
100% |
603
0.73 IPS |
|
|
Object Detection (F32)
|
100% |
192
14.3 IPS |
|
|
Object Detection (F16)
|
100% |
258
19.3 IPS |
|
|
Object Detection (I8)
|
62% |
262
19.6 IPS |
|
|
Face Detection (F32)
|
100% |
1086
12.9 IPS |
|
|
Face Detection (F16)
|
98% |
1196
14.2 IPS |
|
|
Face Detection (I8)
|
86% |
1085
12.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
755
5.86 IPS |
|
|
Depth Estimation (F16)
|
100% |
914
7.09 IPS |
|
|
Depth Estimation (I8)
|
95% |
914
7.09 IPS |
|
|
Style Transfer (F32)
|
100% |
1970
2.59 IPS |
|
|
Style Transfer (F16)
|
100% |
2530
3.33 IPS |
|
|
Style Transfer (I8)
|
98% |
2516
3.31 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
395
14.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
524
18.7 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
512
18.3 IPS |
|
|
Text Classification (F32)
|
100% |
298
428.9 IPS |
|
|
Text Classification (F16)
|
100% |
299
429.4 IPS |
|
|
Text Classification (I8)
|
92% |
511
734.6 IPS |
|
|
Machine Translation (F32)
|
100% |
479
8.82 IPS |
|
|
Machine Translation (F16)
|
100% |
473
8.70 IPS |
|
|
Machine Translation (I8)
|
64% |
400
7.37 IPS |
