Google nissa
Geekbench ML Score
403
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:14 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
254
47.5 IPS |
|
|
Image Classification (F16)
|
100% |
390
72.9 IPS |
|
|
Image Classification (I8)
|
97% |
376
70.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
300
5.02 IPS |
|
|
Image Segmentation (F16)
|
100% |
509
8.51 IPS |
|
|
Image Segmentation (I8)
|
98% |
402
6.71 IPS |
|
|
Pose Estimation (F32)
|
100% |
381
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
718
0.87 IPS |
|
|
Pose Estimation (I8)
|
100% |
717
0.87 IPS |
|
|
Object Detection (F32)
|
100% |
191
14.3 IPS |
|
|
Object Detection (F16)
|
100% |
273
20.4 IPS |
|
|
Object Detection (I8)
|
65% |
310
23.1 IPS |
|
|
Face Detection (F32)
|
100% |
711
8.45 IPS |
|
|
Face Detection (F16)
|
98% |
1095
13.0 IPS |
|
|
Face Detection (I8)
|
85% |
961
11.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
539
4.18 IPS |
|
|
Depth Estimation (F16)
|
100% |
946
7.34 IPS |
|
|
Depth Estimation (I8)
|
94% |
938
7.27 IPS |
|
|
Style Transfer (F32)
|
100% |
1255
1.65 IPS |
|
|
Style Transfer (F16)
|
100% |
2231
2.93 IPS |
|
|
Style Transfer (I8)
|
98% |
2167
2.85 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
268
9.56 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
478
17.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
450
16.1 IPS |
|
|
Text Classification (F32)
|
100% |
103
148.0 IPS |
|
|
Text Classification (F16)
|
100% |
103
147.9 IPS |
|
|
Text Classification (I8)
|
92% |
44
62.6 IPS |
|
|
Machine Translation (F32)
|
100% |
212
3.90 IPS |
|
|
Machine Translation (F16)
|
100% |
213
3.92 IPS |
|
|
Machine Translation (I8)
|
64% |
76
1.40 IPS |
