Google nissa
Geekbench ML Score
400
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 08 2024 10:21 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% |
247
46.3 IPS |
|
|
Image Classification (F16)
|
100% |
393
73.6 IPS |
|
|
Image Classification (I8)
|
97% |
398
74.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
297
4.96 IPS |
|
|
Image Segmentation (F16)
|
100% |
519
8.67 IPS |
|
|
Image Segmentation (I8)
|
98% |
397
6.63 IPS |
|
|
Pose Estimation (F32)
|
100% |
383
0.46 IPS |
|
|
Pose Estimation (F16)
|
100% |
718
0.87 IPS |
|
|
Pose Estimation (I8)
|
100% |
717
0.87 IPS |
|
|
Object Detection (F32)
|
100% |
192
14.3 IPS |
|
|
Object Detection (F16)
|
100% |
269
20.1 IPS |
|
|
Object Detection (I8)
|
65% |
263
19.7 IPS |
|
|
Face Detection (F32)
|
100% |
698
8.30 IPS |
|
|
Face Detection (F16)
|
98% |
1091
13.0 IPS |
|
|
Face Detection (I8)
|
85% |
957
11.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
538
4.17 IPS |
|
|
Depth Estimation (F16)
|
100% |
948
7.35 IPS |
|
|
Depth Estimation (I8)
|
94% |
938
7.28 IPS |
|
|
Style Transfer (F32)
|
100% |
1259
1.66 IPS |
|
|
Style Transfer (F16)
|
100% |
2225
2.93 IPS |
|
|
Style Transfer (I8)
|
98% |
2183
2.87 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
264
9.43 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
478
17.1 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
453
16.2 IPS |
|
|
Text Classification (F32)
|
100% |
103
148.2 IPS |
|
|
Text Classification (F16)
|
100% |
103
148.4 IPS |
|
|
Text Classification (I8)
|
92% |
43
62.2 IPS |
|
|
Machine Translation (F32)
|
100% |
215
3.96 IPS |
|
|
Machine Translation (F16)
|
100% |
214
3.94 IPS |
|
|
Machine Translation (I8)
|
64% |
76
1.40 IPS |
