Google nissa
Geekbench ML Score
433
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:32 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 | 6.83 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
401
75.1 IPS |
|
|
Image Classification (F16)
|
100% |
397
74.2 IPS |
|
|
Image Classification (I8)
|
97% |
180
33.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
454
7.59 IPS |
|
|
Image Segmentation (F16)
|
100% |
458
7.65 IPS |
|
|
Image Segmentation (I8)
|
98% |
172
2.87 IPS |
|
|
Pose Estimation (F32)
|
100% |
652
0.79 IPS |
|
|
Pose Estimation (F16)
|
100% |
650
0.79 IPS |
|
|
Pose Estimation (I8)
|
100% |
589
0.71 IPS |
|
|
Object Detection (F32)
|
100% |
246
18.4 IPS |
|
|
Object Detection (F16)
|
100% |
307
22.9 IPS |
|
|
Object Detection (I8)
|
61% |
212
15.8 IPS |
|
|
Face Detection (F32)
|
100% |
863
10.3 IPS |
|
|
Face Detection (F16)
|
100% |
875
10.4 IPS |
|
|
Face Detection (I8)
|
86% |
343
4.08 IPS |
|
|
Depth Estimation (F32)
|
100% |
708
5.49 IPS |
|
|
Depth Estimation (F16)
|
100% |
701
5.43 IPS |
|
|
Depth Estimation (I8)
|
95% |
485
3.76 IPS |
|
|
Style Transfer (F32)
|
100% |
1114
1.47 IPS |
|
|
Style Transfer (F16)
|
100% |
1060
1.39 IPS |
|
|
Style Transfer (I8)
|
98% |
1256
1.65 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
368
13.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
365
13.0 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
236
8.43 IPS |
|
|
Text Classification (F32)
|
100% |
417
600.0 IPS |
|
|
Text Classification (F16)
|
100% |
411
590.0 IPS |
|
|
Text Classification (I8)
|
92% |
90
129.0 IPS |
|
|
Machine Translation (F32)
|
100% |
667
12.3 IPS |
|
|
Machine Translation (F16)
|
100% |
661
12.2 IPS |
|
|
Machine Translation (I8)
|
64% |
162
2.99 IPS |
