samsung SM-E076B
Geekbench AI Score
220
Single Precision Score
309
Half Precision Score
203
Quantized Score
Geekbench AI 1.6.1 for Android AArch64
Result Information
| Upload Date | February 09 2026 07:20 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | NNAPI |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 16 |
| Model | samsung SM-E076B |
| Model ID | samsung SM-E076B |
| Motherboard | a07x |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 4 part 3339 revision 0 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 6 Cores @ 2.00 GHz |
| Cluster 2 | 2 Cores @ 2.40 GHz |
| Memory Information | |
|---|---|
| Size | 3.40 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
126
23.5 IPS |
|
|
Image Classification (HP)
|
100% |
383
71.2 IPS |
|
|
Image Classification (Q)
|
97% |
68
12.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
236
3.82 IPS |
|
|
Image Segmentation (HP)
|
100% |
145
2.35 IPS |
|
|
Image Segmentation (Q)
|
98% |
79
1.28 IPS |
|
|
Pose Estimation (SP)
|
100% |
903
1.05 IPS |
|
|
Pose Estimation (HP)
|
98% |
2027
2.37 IPS |
|
|
Pose Estimation (Q)
|
70% |
1161
1.48 IPS |
|
|
Object Detection (SP)
|
100% |
147
11.7 IPS |
|
|
Object Detection (HP)
|
100% |
104
8.22 IPS |
|
|
Object Detection (Q)
|
80% |
81
6.59 IPS |
|
|
Face Detection (SP)
|
28% |
36
6.78 IPS |
|
|
Face Detection (HP)
|
100% |
269
3.19 IPS |
|
|
Face Detection (Q)
|
97% |
120
1.43 IPS |
|
|
Depth Estimation (SP)
|
100% |
372
2.87 IPS |
|
|
Depth Estimation (HP)
|
99% |
222
1.71 IPS |
|
|
Depth Estimation (Q)
|
57% |
247
2.69 IPS |
|
|
Style Transfer (SP)
|
100% |
732
0.94 IPS |
|
|
Style Transfer (HP)
|
100% |
372
0.48 IPS |
|
|
Style Transfer (Q)
|
98% |
1750
2.26 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
368
13.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
782
28.9 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
455
16.9 IPS |
|
|
Text Classification (SP)
|
100% |
93
124.1 IPS |
|
|
Text Classification (HP)
|
100% |
167
222.3 IPS |
|
|
Text Classification (Q)
|
93% |
93
125.5 IPS |
|
|
Machine Translation (SP)
|
100% |
205
3.52 IPS |
|
|
Machine Translation (HP)
|
100% |
234
4.03 IPS |
|
|
Machine Translation (Q)
|
55% |
108
2.87 IPS |
