Google Pixel Tablet
Geekbench AI Score
516
Single Precision Score
609
Half Precision Score
605
Quantized Score
Geekbench AI 1.0.0 for Android AArch64
Result Information
| User | pingwinator |
| Upload Date | August 16 2024 01:41 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Google Tensor G2 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Google Pixel Tablet |
| Model ID | Google Pixel Tablet |
| Motherboard | tangorpro |
| 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 | 7.28 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
245
45.5 IPS |
|
|
Image Classification (HP)
|
100% |
243
45.1 IPS |
|
|
Image Classification (Q)
|
97% |
240
44.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
616
9.99 IPS |
|
|
Image Segmentation (HP)
|
100% |
839
13.6 IPS |
|
|
Image Segmentation (Q)
|
98% |
773
12.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
454
0.53 IPS |
|
|
Pose Estimation (HP)
|
100% |
622
0.73 IPS |
|
|
Pose Estimation (Q)
|
96% |
618
0.72 IPS |
|
|
Object Detection (SP)
|
100% |
238
18.8 IPS |
|
|
Object Detection (HP)
|
100% |
294
23.3 IPS |
|
|
Object Detection (Q)
|
92% |
298
23.8 IPS |
|
|
Face Detection (SP)
|
100% |
1092
13.0 IPS |
|
|
Face Detection (HP)
|
100% |
1281
15.2 IPS |
|
|
Face Detection (Q)
|
97% |
1241
14.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
765
5.89 IPS |
|
|
Depth Estimation (HP)
|
99% |
914
7.04 IPS |
|
|
Depth Estimation (Q)
|
72% |
845
7.00 IPS |
|
|
Style Transfer (SP)
|
100% |
2014
2.59 IPS |
|
|
Style Transfer (HP)
|
100% |
2605
3.35 IPS |
|
|
Style Transfer (Q)
|
98% |
2594
3.35 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
374
13.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
474
17.5 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
456
16.9 IPS |
|
|
Text Classification (SP)
|
100% |
294
392.9 IPS |
|
|
Text Classification (HP)
|
100% |
297
396.9 IPS |
|
|
Text Classification (Q)
|
91% |
506
679.9 IPS |
|
|
Machine Translation (SP)
|
100% |
452
7.79 IPS |
|
|
Machine Translation (HP)
|
100% |
439
7.56 IPS |
|
|
Machine Translation (Q)
|
57% |
308
7.53 IPS |
