Google Pixel 7
Geekbench ML Score
584
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 17 2024 12:04 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
323
60.5 IPS |
|
|
Image Classification (F16)
|
100% |
325
60.9 IPS |
|
|
Image Classification (I8)
|
97% |
268
50.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
625
10.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
833
13.9 IPS |
|
|
Image Segmentation (I8)
|
98% |
805
13.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
441
0.53 IPS |
|
|
Pose Estimation (F16)
|
100% |
606
0.73 IPS |
|
|
Pose Estimation (I8)
|
100% |
607
0.74 IPS |
|
|
Object Detection (F32)
|
100% |
206
15.3 IPS |
|
|
Object Detection (F16)
|
100% |
251
18.8 IPS |
|
|
Object Detection (I8)
|
62% |
271
20.3 IPS |
|
|
Face Detection (F32)
|
100% |
989
11.8 IPS |
|
|
Face Detection (F16)
|
98% |
964
11.5 IPS |
|
|
Face Detection (I8)
|
86% |
991
11.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
752
5.83 IPS |
|
|
Depth Estimation (F16)
|
100% |
934
7.24 IPS |
|
|
Depth Estimation (I8)
|
95% |
883
6.85 IPS |
|
|
Style Transfer (F32)
|
100% |
1896
2.49 IPS |
|
|
Style Transfer (F16)
|
100% |
2509
3.30 IPS |
|
|
Style Transfer (I8)
|
98% |
2537
3.34 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
397
14.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
511
18.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
523
18.7 IPS |
|
|
Text Classification (F32)
|
100% |
312
448.3 IPS |
|
|
Text Classification (F16)
|
100% |
312
448.9 IPS |
|
|
Text Classification (I8)
|
92% |
513
736.7 IPS |
|
|
Machine Translation (F32)
|
100% |
496
9.14 IPS |
|
|
Machine Translation (F16)
|
100% |
495
9.11 IPS |
|
|
Machine Translation (I8)
|
64% |
413
7.60 IPS |
