Google Pixel Fold
Geekbench ML Score
2136
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| User | navtiidia |
| Upload Date | August 01 2024 08:45 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | Google Pixel Fold |
| Model ID | Google Pixel Fold |
| Motherboard | felix |
| 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 | 11.20 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
219
41.0 IPS |
|
|
Image Classification (F16)
|
100% |
5426
1.02 KIPS |
|
|
Image Classification (I8)
|
99% |
8383
1.57 KIPS |
|
|
Image Segmentation (F32)
|
100% |
286
4.78 IPS |
|
|
Image Segmentation (F16)
|
100% |
5439
90.8 IPS |
|
|
Image Segmentation (I8)
|
98% |
9331
155.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
380
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
20075
24.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
36778
44.5 IPS |
|
|
Object Detection (F32)
|
100% |
235
17.6 IPS |
|
|
Object Detection (F16)
|
100% |
3056
228.1 IPS |
|
|
Object Detection (I8)
|
65% |
3807
284.2 IPS |
|
|
Face Detection (F32)
|
100% |
535
6.36 IPS |
|
|
Face Detection (F16)
|
100% |
534
6.35 IPS |
|
|
Face Detection (I8)
|
87% |
31345
372.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
477
3.70 IPS |
|
|
Depth Estimation (F16)
|
100% |
23290
180.6 IPS |
|
|
Depth Estimation (I8)
|
94% |
38502
298.6 IPS |
|
|
Style Transfer (F32)
|
100% |
755
0.99 IPS |
|
|
Style Transfer (F16)
|
100% |
1749
2.30 IPS |
|
|
Style Transfer (I8)
|
28% |
3381
4.45 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
251
8.95 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
6790
242.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
15007
535.9 IPS |
|
|
Text Classification (F32)
|
100% |
313
450.3 IPS |
|
|
Text Classification (F16)
|
100% |
1896
2.72 KIPS |
|
|
Text Classification (I8)
|
94% |
2204
3.17 KIPS |
|
|
Machine Translation (F32)
|
100% |
504
9.28 IPS |
|
|
Machine Translation (F16)
|
100% |
510
9.38 IPS |
|
|
Machine Translation (I8)
|
64% |
479
8.81 IPS |
