Realme GT Master
Geekbench ML Score
438
TensorFlow Lite NNAPI Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 26 2024 06:15 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | Realme GT Master |
| Model ID | realme RMX3363 |
| Motherboard | lahaina |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 4 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.11 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
288
53.8 IPS |
|
|
Image Classification (F16)
|
100% |
522
97.7 IPS |
|
|
Image Classification (I8)
|
94% |
17
3.26 IPS |
|
|
Image Segmentation (F32)
|
100% |
487
8.13 IPS |
|
|
Image Segmentation (F16)
|
100% |
748
12.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
356
5.95 IPS |
|
|
Pose Estimation (F32)
|
100% |
836
1.01 IPS |
|
|
Pose Estimation (F16)
|
100% |
3016
3.65 IPS |
|
|
Pose Estimation (I8)
|
100% |
809
0.98 IPS |
|
|
Object Detection (F32)
|
100% |
320
23.9 IPS |
|
|
Object Detection (F16)
|
100% |
508
37.9 IPS |
|
|
Object Detection (I8)
|
0% |
2160
161.2 IPS |
|
|
Face Detection (F32)
|
100% |
759
9.02 IPS |
|
|
Face Detection (F16)
|
97% |
1217
14.5 IPS |
|
|
Face Detection (I8)
|
86% |
732
8.71 IPS |
|
|
Depth Estimation (F32)
|
100% |
438
3.40 IPS |
|
|
Depth Estimation (F16)
|
100% |
525
4.07 IPS |
|
|
Depth Estimation (I8)
|
73% |
7948
61.6 IPS |
|
|
Style Transfer (F32)
|
100% |
1216
1.60 IPS |
|
|
Style Transfer (F16)
|
100% |
1664
2.19 IPS |
|
|
Style Transfer (I8)
|
98% |
1347
1.77 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
525
18.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1498
53.5 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
261
9.33 IPS |
|
|
Text Classification (F32)
|
100% |
3
4.98 IPS |
|
|
Text Classification (F16)
|
100% |
52
75.2 IPS |
|
|
Text Classification (I8)
|
94% |
29
41.1 IPS |
|
|
Machine Translation (F32)
|
100% |
227
4.17 IPS |
|
|
Machine Translation (F16)
|
100% |
290
5.33 IPS |
|
|
Machine Translation (I8)
|
64% |
372
6.85 IPS |
