Samsung Galaxy A33
Geekbench ML Score
294
TensorFlow Lite CPU Inference Score
Geekbench ML 0.6.0 for Android AArch64
Result Information
| Upload Date | January 16 2024 11:35 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Samsung Galaxy A33 |
| Model ID | samsung SM-A336E |
| Motherboard | s5e8825 |
| Governor | energy_aware |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3393 revision 1 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 7.22 GB |
| Inference Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
147
27.6 IPS |
|
|
Image Classification (F16)
|
100% |
140
26.1 IPS |
|
|
Image Classification (I8)
|
97% |
453
84.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
242
4.03 IPS |
|
|
Image Segmentation (F16)
|
100% |
220
3.67 IPS |
|
|
Image Segmentation (I8)
|
98% |
288
4.81 IPS |
|
|
Pose Estimation (F32)
|
100% |
344
0.42 IPS |
|
|
Pose Estimation (F16)
|
100% |
338
0.41 IPS |
|
|
Pose Estimation (I8)
|
100% |
1845
2.23 IPS |
|
|
Object Detection (F32)
|
100% |
179
13.3 IPS |
|
|
Object Detection (F16)
|
100% |
168
12.6 IPS |
|
|
Object Detection (I8)
|
61% |
354
26.4 IPS |
|
|
Face Detection (F32)
|
100% |
340
4.04 IPS |
|
|
Face Detection (F16)
|
100% |
352
4.18 IPS |
|
|
Face Detection (I8)
|
86% |
1089
12.9 IPS |
|
|
Depth Estimation (F32)
|
100% |
299
2.32 IPS |
|
|
Depth Estimation (F16)
|
100% |
220
1.70 IPS |
|
|
Depth Estimation (I8)
|
95% |
373
2.89 IPS |
|
|
Style Transfer (F32)
|
100% |
489
0.64 IPS |
|
|
Style Transfer (F16)
|
100% |
602
0.79 IPS |
|
|
Style Transfer (I8)
|
98% |
1749
2.30 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
109
3.89 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
101
3.60 IPS |
|
|
Image Super-Resolution (I8)
|
98% |
234
8.37 IPS |
|
|
Text Classification (F32)
|
100% |
240
345.2 IPS |
|
|
Text Classification (F16)
|
100% |
111
159.9 IPS |
|
|
Text Classification (I8)
|
92% |
324
465.5 IPS |
|
|
Machine Translation (F32)
|
100% |
320
5.89 IPS |
|
|
Machine Translation (F16)
|
100% |
275
5.06 IPS |
|
|
Machine Translation (I8)
|
64% |
108
1.99 IPS |
