realme RMX3372
Geekbench ML Score
594
TensorFlow Lite GPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | March 08 2025 12:05 PM |
| Views | 5 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | realme RMX3372 |
| Model ID | realme RMX3372 |
| Motherboard | kona |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3341 revision 0 |
| Base Frequency | 1.80 GHz |
| Cluster 1 | 4 Cores @ 1.80 GHz |
| Cluster 2 | 3 Cores @ 2.42 GHz |
| Cluster 3 | 1 Core @ 3.19 GHz |
| Memory Information | |
|---|---|
| Size | 7.34 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
280
52.5 IPS |
|
|
Image Classification (F16)
|
100% |
397
74.4 IPS |
|
|
Image Classification (I8)
|
97% |
403
75.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
353
5.89 IPS |
|
|
Image Segmentation (F16)
|
100% |
690
11.5 IPS |
|
|
Image Segmentation (I8)
|
98% |
656
11.0 IPS |
|
|
Pose Estimation (F32)
|
100% |
540
0.65 IPS |
|
|
Pose Estimation (F16)
|
100% |
1087
1.32 IPS |
|
|
Pose Estimation (I8)
|
100% |
1083
1.31 IPS |
|
|
Object Detection (F32)
|
100% |
205
15.3 IPS |
|
|
Object Detection (F16)
|
100% |
214
16.0 IPS |
|
|
Object Detection (I8)
|
62% |
240
17.9 IPS |
|
|
Face Detection (F32)
|
100% |
696
8.28 IPS |
|
|
Face Detection (F16)
|
97% |
1224
14.5 IPS |
|
|
Face Detection (I8)
|
87% |
1209
14.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
655
5.08 IPS |
|
|
Depth Estimation (F16)
|
100% |
1255
9.73 IPS |
|
|
Depth Estimation (I8)
|
95% |
1248
9.68 IPS |
|
|
Style Transfer (F32)
|
100% |
1225
1.61 IPS |
|
|
Style Transfer (F16)
|
100% |
3209
4.22 IPS |
|
|
Style Transfer (I8)
|
98% |
2944
3.87 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
329
11.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
744
26.6 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
700
25.0 IPS |
|
|
Text Classification (F32)
|
100% |
233
335.0 IPS |
|
|
Text Classification (F16)
|
100% |
233
335.4 IPS |
|
|
Text Classification (I8)
|
92% |
405
582.4 IPS |
|
|
Machine Translation (F32)
|
100% |
388
7.15 IPS |
|
|
Machine Translation (F16)
|
100% |
392
7.21 IPS |
|
|
Machine Translation (I8)
|
64% |
495
9.11 IPS |
