Realme GT Master
Geekbench ML Score
172
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | May 26 2024 06:08 PM |
| Views | 1 |
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 | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
73
13.6 IPS |
|
|
Image Classification (F16)
|
100% |
73
13.6 IPS |
|
|
Image Classification (I8)
|
97% |
85
16.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
226
3.78 IPS |
|
|
Image Segmentation (F16)
|
100% |
228
3.80 IPS |
|
|
Image Segmentation (I8)
|
98% |
309
5.16 IPS |
|
|
Pose Estimation (F32)
|
100% |
446
0.54 IPS |
|
|
Pose Estimation (F16)
|
100% |
440
0.53 IPS |
|
|
Pose Estimation (I8)
|
100% |
1754
2.12 IPS |
|
|
Object Detection (F32)
|
100% |
103
7.66 IPS |
|
|
Object Detection (F16)
|
100% |
102
7.65 IPS |
|
|
Object Detection (I8)
|
61% |
136
10.1 IPS |
|
|
Face Detection (F32)
|
100% |
284
3.38 IPS |
|
|
Face Detection (F16)
|
100% |
284
3.37 IPS |
|
|
Face Detection (I8)
|
86% |
432
5.13 IPS |
|
|
Depth Estimation (F32)
|
100% |
291
2.25 IPS |
|
|
Depth Estimation (F16)
|
100% |
298
2.31 IPS |
|
|
Depth Estimation (I8)
|
95% |
453
3.51 IPS |
|
|
Style Transfer (F32)
|
100% |
765
1.01 IPS |
|
|
Style Transfer (F16)
|
100% |
769
1.01 IPS |
|
|
Style Transfer (I8)
|
98% |
2266
2.98 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
174
6.21 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
174
6.20 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
283
10.1 IPS |
|
|
Text Classification (F32)
|
100% |
15
21.4 IPS |
|
|
Text Classification (F16)
|
100% |
15
21.4 IPS |
|
|
Text Classification (I8)
|
92% |
17
24.3 IPS |
|
|
Machine Translation (F32)
|
100% |
38
0.69 IPS |
|
|
Machine Translation (F16)
|
100% |
38
0.69 IPS |
|
|
Machine Translation (I8)
|
64% |
40
0.74 IPS |
