Google Pixel Fold
Geekbench AI Score
1028
Single Precision Score
1028
Half Precision Score
1884
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| User | BulbousSum |
| Upload Date | December 14 2024 09:44 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Google Tensor G2 |
| 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 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
436
81.2 IPS |
|
|
Image Classification (HP)
|
100% |
520
96.7 IPS |
|
|
Image Classification (Q)
|
100% |
1506
280.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
626
10.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
626
10.2 IPS |
|
|
Image Segmentation (Q)
|
98% |
1686
27.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
2412
2.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
2304
2.69 IPS |
|
|
Pose Estimation (Q)
|
84% |
3101
3.68 IPS |
|
|
Object Detection (SP)
|
100% |
443
35.1 IPS |
|
|
Object Detection (HP)
|
100% |
489
38.8 IPS |
|
|
Object Detection (Q)
|
83% |
1417
114.5 IPS |
|
|
Face Detection (SP)
|
100% |
1571
18.7 IPS |
|
|
Face Detection (HP)
|
100% |
1537
18.3 IPS |
|
|
Face Detection (Q)
|
95% |
3389
40.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
2022
15.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
2002
15.4 IPS |
|
|
Depth Estimation (Q)
|
64% |
3263
29.9 IPS |
|
|
Style Transfer (SP)
|
89% |
3686
4.78 IPS |
|
|
Style Transfer (HP)
|
89% |
3313
4.30 IPS |
|
|
Style Transfer (Q)
|
98% |
7235
9.33 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
981
36.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
969
35.8 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
1814
67.2 IPS |
|
|
Text Classification (SP)
|
100% |
493
658.2 IPS |
|
|
Text Classification (HP)
|
100% |
514
685.5 IPS |
|
|
Text Classification (Q)
|
88% |
850
1.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
801
13.8 IPS |
|
|
Machine Translation (HP)
|
100% |
710
12.2 IPS |
|
|
Machine Translation (Q)
|
50% |
411
14.6 IPS |
