Google Pixel 8a
Geekbench ML Score
670
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:18 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Google Pixel 8a |
| Model ID | Google Pixel 8a |
| Motherboard | akita |
| Governor | sched_pixel |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 9 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3406 revision 0 |
| Base Frequency | 1.70 GHz |
| Cluster 1 | 4 Cores @ 1.70 GHz |
| Cluster 2 | 4 Cores @ 2.37 GHz |
| Cluster 3 | 1 Core @ 2.91 GHz |
| Memory Information | |
|---|---|
| Size | 7.40 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
258
48.2 IPS |
|
|
Image Classification (F16)
|
100% |
448
83.9 IPS |
|
|
Image Classification (I8)
|
97% |
429
80.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
557
9.30 IPS |
|
|
Image Segmentation (F16)
|
100% |
639
10.7 IPS |
|
|
Image Segmentation (I8)
|
98% |
622
10.4 IPS |
|
|
Pose Estimation (F32)
|
100% |
454
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
664
0.80 IPS |
|
|
Pose Estimation (I8)
|
100% |
661
0.80 IPS |
|
|
Object Detection (F32)
|
100% |
271
20.2 IPS |
|
|
Object Detection (F16)
|
100% |
291
21.8 IPS |
|
|
Object Detection (I8)
|
62% |
366
27.3 IPS |
|
|
Face Detection (F32)
|
100% |
1064
12.6 IPS |
|
|
Face Detection (F16)
|
98% |
1127
13.4 IPS |
|
|
Face Detection (I8)
|
86% |
1277
15.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
876
6.80 IPS |
|
|
Depth Estimation (F16)
|
100% |
1046
8.11 IPS |
|
|
Depth Estimation (I8)
|
95% |
1057
8.20 IPS |
|
|
Style Transfer (F32)
|
100% |
2525
3.32 IPS |
|
|
Style Transfer (F16)
|
100% |
3074
4.04 IPS |
|
|
Style Transfer (I8)
|
98% |
3055
4.02 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
506
18.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
571
20.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
590
21.1 IPS |
|
|
Text Classification (F32)
|
100% |
392
563.3 IPS |
|
|
Text Classification (F16)
|
100% |
387
556.5 IPS |
|
|
Text Classification (I8)
|
92% |
580
833.0 IPS |
|
|
Machine Translation (F32)
|
100% |
593
10.9 IPS |
|
|
Machine Translation (F16)
|
100% |
568
10.4 IPS |
|
|
Machine Translation (I8)
|
64% |
554
10.2 IPS |
