Google nissa
Geekbench ML Score
446
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:32 PM |
| Views | 1 |
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% |
410
76.7 IPS |
|
|
Image Classification (I8)
|
97% |
183
34.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
466
7.78 IPS |
|
|
Image Segmentation (F16)
|
100% |
465
7.76 IPS |
|
|
Image Segmentation (I8)
|
98% |
172
2.87 IPS |
|
|
Pose Estimation (F32)
|
100% |
664
0.80 IPS |
|
|
Pose Estimation (F16)
|
100% |
651
0.79 IPS |
|
|
Pose Estimation (I8)
|
100% |
618
0.75 IPS |
|
|
Object Detection (F32)
|
100% |
317
23.7 IPS |
|
|
Object Detection (F16)
|
100% |
318
23.8 IPS |
|
|
Object Detection (I8)
|
61% |
218
16.3 IPS |
|
|
Face Detection (F32)
|
100% |
870
10.3 IPS |
|
|
Face Detection (F16)
|
100% |
861
10.2 IPS |
|
|
Face Detection (I8)
|
86% |
358
4.26 IPS |
|
|
Depth Estimation (F32)
|
100% |
733
5.69 IPS |
|
|
Depth Estimation (F16)
|
100% |
728
5.65 IPS |
|
|
Depth Estimation (I8)
|
95% |
502
3.89 IPS |
|
|
Style Transfer (F32)
|
100% |
1098
1.44 IPS |
|
|
Style Transfer (F16)
|
100% |
1108
1.46 IPS |
|
|
Style Transfer (I8)
|
98% |
1344
1.77 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
373
13.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
375
13.4 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
237
8.48 IPS |
|
|
Text Classification (F32)
|
100% |
421
605.7 IPS |
|
|
Text Classification (F16)
|
100% |
418
600.6 IPS |
|
|
Text Classification (I8)
|
92% |
90
128.9 IPS |
|
|
Machine Translation (F32)
|
100% |
695
12.8 IPS |
|
|
Machine Translation (F16)
|
100% |
671
12.3 IPS |
|
|
Machine Translation (I8)
|
64% |
167
3.06 IPS |
