Google nissa
Geekbench ML Score
451
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 03 2024 04:16 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Google nissa |
| Model ID | Google nissa |
| Motherboard | joxer |
| CPU Information | |
|---|---|
| Name | placeholder |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 78 architecture 8 variant 2 part 0 revision 1 |
| Base Frequency | 0 MHz |
| Cluster 1 | 8 Cores |
| Memory Information | |
|---|---|
| Size | 6.84 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
430
80.6 IPS |
|
|
Image Classification (F16)
|
100% |
426
79.8 IPS |
|
|
Image Classification (I8)
|
97% |
186
34.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
472
7.89 IPS |
|
|
Image Segmentation (F16)
|
100% |
466
7.78 IPS |
|
|
Image Segmentation (I8)
|
98% |
170
2.83 IPS |
|
|
Pose Estimation (F32)
|
100% |
601
0.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
601
0.73 IPS |
|
|
Pose Estimation (I8)
|
100% |
632
0.77 IPS |
|
|
Object Detection (F32)
|
100% |
318
23.7 IPS |
|
|
Object Detection (F16)
|
100% |
321
23.9 IPS |
|
|
Object Detection (I8)
|
61% |
220
16.4 IPS |
|
|
Face Detection (F32)
|
100% |
876
10.4 IPS |
|
|
Face Detection (F16)
|
100% |
894
10.6 IPS |
|
|
Face Detection (I8)
|
86% |
342
4.06 IPS |
|
|
Depth Estimation (F32)
|
100% |
752
5.83 IPS |
|
|
Depth Estimation (F16)
|
100% |
722
5.60 IPS |
|
|
Depth Estimation (I8)
|
95% |
488
3.79 IPS |
|
|
Style Transfer (F32)
|
100% |
1076
1.42 IPS |
|
|
Style Transfer (F16)
|
100% |
1166
1.53 IPS |
|
|
Style Transfer (I8)
|
98% |
1346
1.77 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
397
14.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
398
14.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
243
8.67 IPS |
|
|
Text Classification (F32)
|
100% |
437
627.4 IPS |
|
|
Text Classification (F16)
|
100% |
439
630.4 IPS |
|
|
Text Classification (I8)
|
92% |
91
130.5 IPS |
|
|
Machine Translation (F32)
|
100% |
734
13.5 IPS |
|
|
Machine Translation (F16)
|
100% |
711
13.1 IPS |
|
|
Machine Translation (I8)
|
64% |
163
3.00 IPS |
