Google Pixel 8
Geekbench ML Score
2515
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:16 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Google Pixel 8 |
| Model ID | Google Pixel 8 |
| Motherboard | shiba |
| 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% |
256
47.9 IPS |
|
|
Image Classification (F16)
|
100% |
4111
769.2 IPS |
|
|
Image Classification (I8)
|
99% |
4485
839.3 IPS |
|
|
Image Segmentation (F32)
|
100% |
317
5.29 IPS |
|
|
Image Segmentation (F16)
|
100% |
9663
161.4 IPS |
|
|
Image Segmentation (I8)
|
98% |
23411
391.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
353
0.43 IPS |
|
|
Pose Estimation (F16)
|
100% |
31480
38.1 IPS |
|
|
Pose Estimation (I8)
|
100% |
61275
74.2 IPS |
|
|
Object Detection (F32)
|
100% |
222
16.6 IPS |
|
|
Object Detection (F16)
|
100% |
3084
230.2 IPS |
|
|
Object Detection (I8)
|
65% |
3567
266.3 IPS |
|
|
Face Detection (F32)
|
100% |
580
6.89 IPS |
|
|
Face Detection (F16)
|
98% |
19757
234.9 IPS |
|
|
Face Detection (I8)
|
87% |
31574
375.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
511
3.96 IPS |
|
|
Depth Estimation (F16)
|
100% |
33302
258.3 IPS |
|
|
Depth Estimation (I8)
|
94% |
40257
312.2 IPS |
|
|
Style Transfer (F32)
|
100% |
771
1.01 IPS |
|
|
Style Transfer (F16)
|
100% |
1815
2.39 IPS |
|
|
Style Transfer (I8)
|
28% |
3187
4.19 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
289
10.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10505
375.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
19646
701.6 IPS |
|
|
Text Classification (F32)
|
100% |
281
403.4 IPS |
|
|
Text Classification (F16)
|
100% |
836
1.20 KIPS |
|
|
Text Classification (I8)
|
94% |
728
1.05 KIPS |
|
|
Machine Translation (F32)
|
100% |
566
10.4 IPS |
|
|
Machine Translation (F16)
|
100% |
550
10.1 IPS |
|
|
Machine Translation (I8)
|
64% |
529
9.74 IPS |
