Google Pixel 8a
Geekbench ML Score
2060
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | M91 |
| Upload Date | July 27 2024 12:29 AM |
| Views | 2 |
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 | 7.42 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
232
43.5 IPS |
|
|
Image Classification (F16)
|
100% |
3077
575.8 IPS |
|
|
Image Classification (I8)
|
99% |
4583
857.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
281
4.70 IPS |
|
|
Image Segmentation (F16)
|
100% |
6815
113.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
16663
278.3 IPS |
|
|
Pose Estimation (F32)
|
100% |
351
0.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
23691
28.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
46927
56.8 IPS |
|
|
Object Detection (F32)
|
100% |
211
15.7 IPS |
|
|
Object Detection (F16)
|
100% |
2170
162.0 IPS |
|
|
Object Detection (I8)
|
65% |
2271
169.6 IPS |
|
|
Face Detection (F32)
|
100% |
565
6.71 IPS |
|
|
Face Detection (F16)
|
98% |
13717
163.1 IPS |
|
|
Face Detection (I8)
|
87% |
24601
292.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
478
3.71 IPS |
|
|
Depth Estimation (F16)
|
100% |
27131
210.4 IPS |
|
|
Depth Estimation (I8)
|
94% |
33643
260.9 IPS |
|
|
Style Transfer (F32)
|
100% |
476
0.63 IPS |
|
|
Style Transfer (F16)
|
100% |
1875
2.47 IPS |
|
|
Style Transfer (I8)
|
28% |
3199
4.21 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
276
9.85 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
8188
292.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
14904
532.3 IPS |
|
|
Text Classification (F32)
|
100% |
323
463.6 IPS |
|
|
Text Classification (F16)
|
100% |
677
973.5 IPS |
|
|
Text Classification (I8)
|
94% |
720
1.04 KIPS |
|
|
Machine Translation (F32)
|
100% |
449
8.26 IPS |
|
|
Machine Translation (F16)
|
100% |
214
3.93 IPS |
|
|
Machine Translation (I8)
|
64% |
514
9.47 IPS |
