Google brya
Geekbench ML Score
451
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 24 2024 12:06 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Google brya |
| Model ID | Google brya |
| Motherboard | redrix |
| CPU Information | |
|---|---|
| Name | placeholder |
| Topology | 1 Processor, 12 Cores |
| Identifier | ARM implementer 78 architecture 8 variant 2 part 0 revision 1 |
| Base Frequency | 0 MHz |
| Cluster 1 | 12 Cores |
| Memory Information | |
|---|---|
| Size | 6.33 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
375
70.1 IPS |
|
|
Image Classification (F16)
|
100% |
215
40.2 IPS |
|
|
Image Classification (I8)
|
97% |
133
24.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
532
8.89 IPS |
|
|
Image Segmentation (F16)
|
100% |
522
8.72 IPS |
|
|
Image Segmentation (I8)
|
98% |
194
3.25 IPS |
|
|
Pose Estimation (F32)
|
100% |
694
0.84 IPS |
|
|
Pose Estimation (F16)
|
100% |
699
0.85 IPS |
|
|
Pose Estimation (I8)
|
100% |
603
0.73 IPS |
|
|
Object Detection (F32)
|
100% |
394
29.4 IPS |
|
|
Object Detection (F16)
|
100% |
393
29.3 IPS |
|
|
Object Detection (I8)
|
61% |
169
12.6 IPS |
|
|
Face Detection (F32)
|
100% |
963
11.5 IPS |
|
|
Face Detection (F16)
|
100% |
990
11.8 IPS |
|
|
Face Detection (I8)
|
86% |
317
3.77 IPS |
|
|
Depth Estimation (F32)
|
100% |
876
6.79 IPS |
|
|
Depth Estimation (F16)
|
100% |
868
6.73 IPS |
|
|
Depth Estimation (I8)
|
95% |
502
3.89 IPS |
|
|
Style Transfer (F32)
|
100% |
1196
1.57 IPS |
|
|
Style Transfer (F16)
|
100% |
1192
1.57 IPS |
|
|
Style Transfer (I8)
|
98% |
1190
1.57 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
477
17.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
489
17.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
262
9.35 IPS |
|
|
Text Classification (F32)
|
100% |
402
577.1 IPS |
|
|
Text Classification (F16)
|
100% |
385
553.3 IPS |
|
|
Text Classification (I8)
|
92% |
77
111.1 IPS |
|
|
Machine Translation (F32)
|
100% |
591
10.9 IPS |
|
|
Machine Translation (F16)
|
100% |
660
12.1 IPS |
|
|
Machine Translation (I8)
|
64% |
178
3.28 IPS |
