realme RMX3312
Geekbench ML Score
594
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | July 26 2024 09:33 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | realme RMX3312 |
| Model ID | realme RMX3312 |
| Motherboard | lahaina |
| Governor | uag |
| CPU Information | |
|---|---|
| Name | ARM Qualcomm |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3396 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 @ 2.84 GHz |
| Memory Information | |
|---|---|
| Size | 7.10 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
273
51.1 IPS |
|
|
Image Classification (F16)
|
100% |
260
48.7 IPS |
|
|
Image Classification (I8)
|
97% |
624
116.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
356
5.95 IPS |
|
|
Image Segmentation (F16)
|
100% |
365
6.09 IPS |
|
|
Image Segmentation (I8)
|
98% |
506
8.46 IPS |
|
|
Pose Estimation (F32)
|
100% |
603
0.73 IPS |
|
|
Pose Estimation (F16)
|
100% |
608
0.74 IPS |
|
|
Pose Estimation (I8)
|
100% |
2822
3.42 IPS |
|
|
Object Detection (F32)
|
100% |
272
20.3 IPS |
|
|
Object Detection (F16)
|
100% |
309
23.1 IPS |
|
|
Object Detection (I8)
|
61% |
800
59.7 IPS |
|
|
Face Detection (F32)
|
100% |
627
7.46 IPS |
|
|
Face Detection (F16)
|
100% |
619
7.36 IPS |
|
|
Face Detection (I8)
|
86% |
1517
18.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
646
5.01 IPS |
|
|
Depth Estimation (F16)
|
100% |
666
5.16 IPS |
|
|
Depth Estimation (I8)
|
95% |
1469
11.4 IPS |
|
|
Style Transfer (F32)
|
100% |
1100
1.45 IPS |
|
|
Style Transfer (F16)
|
100% |
1159
1.52 IPS |
|
|
Style Transfer (I8)
|
98% |
2344
3.08 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
397
14.2 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
369
13.2 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
1230
43.9 IPS |
|
|
Text Classification (F32)
|
100% |
328
471.5 IPS |
|
|
Text Classification (F16)
|
100% |
332
477.0 IPS |
|
|
Text Classification (I8)
|
92% |
289
415.8 IPS |
|
|
Machine Translation (F32)
|
100% |
696
12.8 IPS |
|
|
Machine Translation (F16)
|
100% |
695
12.8 IPS |
|
|
Machine Translation (I8)
|
64% |
272
5.00 IPS |
