Gtel Gtel Delta 16
Geekbench AI Score
272
Single Precision Score
265
Half Precision Score
288
Quantized Score
Geekbench AI 1.2.0 for Android AArch64
Result Information
| Upload Date | June 20 2025 08:08 AM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM MT6765 |
| System Information | |
|---|---|
| Operating System | Android 14 |
| Model | Gtel Gtel Delta 16 |
| Model ID | Gtel Gtel Delta 16 |
| Motherboard | pri_board |
| CPU Information | |
|---|---|
| Name | ARM MT6765 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores @ 1.60 GHz |
| Cluster 2 | 4 Cores @ 2.20 GHz |
| Memory Information | |
|---|---|
| Size | 5.62 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
135
25.0 IPS |
|
|
Image Classification (HP)
|
100% |
119
22.1 IPS |
|
|
Image Classification (Q)
|
100% |
197
36.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
179
2.91 IPS |
|
|
Image Segmentation (HP)
|
100% |
186
3.01 IPS |
|
|
Image Segmentation (Q)
|
98% |
306
4.97 IPS |
|
|
Pose Estimation (SP)
|
100% |
672
0.78 IPS |
|
|
Pose Estimation (HP)
|
100% |
671
0.78 IPS |
|
|
Pose Estimation (Q)
|
84% |
497
0.59 IPS |
|
|
Object Detection (SP)
|
100% |
134
10.7 IPS |
|
|
Object Detection (HP)
|
100% |
146
11.6 IPS |
|
|
Object Detection (Q)
|
83% |
199
16.0 IPS |
|
|
Face Detection (SP)
|
100% |
322
3.83 IPS |
|
|
Face Detection (HP)
|
100% |
298
3.54 IPS |
|
|
Face Detection (Q)
|
95% |
543
6.49 IPS |
|
|
Depth Estimation (SP)
|
100% |
471
3.63 IPS |
|
|
Depth Estimation (HP)
|
99% |
460
3.55 IPS |
|
|
Depth Estimation (Q)
|
64% |
468
4.29 IPS |
|
|
Style Transfer (SP)
|
89% |
1221
1.58 IPS |
|
|
Style Transfer (HP)
|
89% |
1217
1.58 IPS |
|
|
Style Transfer (Q)
|
98% |
1189
1.53 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
211
7.80 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
213
7.86 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
268
9.94 IPS |
|
|
Text Classification (SP)
|
100% |
144
192.0 IPS |
|
|
Text Classification (HP)
|
100% |
125
167.3 IPS |
|
|
Text Classification (Q)
|
88% |
121
162.7 IPS |
|
|
Machine Translation (SP)
|
100% |
186
3.21 IPS |
|
|
Machine Translation (HP)
|
100% |
183
3.16 IPS |
|
|
Machine Translation (Q)
|
50% |
68
2.40 IPS |
