Google Pixel 9 Pro Fold
Geekbench ML Score
2642
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | August 28 2024 11:00 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Google Pixel 9 Pro Fold |
| Model ID | Google Pixel 9 Pro Fold |
| Motherboard | comet |
| Governor | sched_pixel |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3458 revision 1 |
| Base Frequency | 1.95 GHz |
| Cluster 1 | 4 Cores @ 1.95 GHz |
| Cluster 2 | 3 Cores @ 2.60 GHz |
| Cluster 3 | 1 Core @ 3.10 GHz |
| Memory Information | |
|---|---|
| Size | 15.19 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
280
52.5 IPS |
|
|
Image Classification (F16)
|
100% |
4685
876.6 IPS |
|
|
Image Classification (I8)
|
99% |
5823
1.09 KIPS |
|
|
Image Segmentation (F32)
|
100% |
351
5.86 IPS |
|
|
Image Segmentation (F16)
|
100% |
9109
152.1 IPS |
|
|
Image Segmentation (I8)
|
98% |
22220
371.1 IPS |
|
|
Pose Estimation (F32)
|
100% |
454
0.55 IPS |
|
|
Pose Estimation (F16)
|
100% |
30963
37.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
62608
75.8 IPS |
|
|
Object Detection (F32)
|
100% |
284
21.2 IPS |
|
|
Object Detection (F16)
|
100% |
2919
217.9 IPS |
|
|
Object Detection (I8)
|
65% |
2566
191.6 IPS |
|
|
Face Detection (F32)
|
100% |
648
7.71 IPS |
|
|
Face Detection (F16)
|
98% |
14769
175.6 IPS |
|
|
Face Detection (I8)
|
87% |
26298
312.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
585
4.54 IPS |
|
|
Depth Estimation (F16)
|
100% |
34565
268.0 IPS |
|
|
Depth Estimation (I8)
|
94% |
48629
377.1 IPS |
|
|
Style Transfer (F32)
|
100% |
854
1.12 IPS |
|
|
Style Transfer (F16)
|
100% |
856
1.13 IPS |
|
|
Style Transfer (I8)
|
28% |
3674
4.83 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
338
12.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
10983
392.3 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
20610
736.0 IPS |
|
|
Text Classification (F32)
|
100% |
409
588.1 IPS |
|
|
Text Classification (F16)
|
100% |
1012
1.46 KIPS |
|
|
Text Classification (I8)
|
94% |
866
1.24 KIPS |
|
|
Machine Translation (F32)
|
100% |
635
11.7 IPS |
|
|
Machine Translation (F16)
|
100% |
631
11.6 IPS |
|
|
Machine Translation (I8)
|
64% |
615
11.3 IPS |
