FCNT M08
Geekbench AI Score
1748
Single Precision Score
2142
Half Precision Score
3096
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | Keitan924111 |
| Upload Date | March 06 2026 04:53 AM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | CPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 15 |
| Model | FCNT M08 |
| Model ID | FCNT M08 |
| Motherboard | M08 |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 8 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 1 part 3405 revision 0 |
| Base Frequency | 2.20 GHz |
| Cluster 1 | 4 Cores @ 2.20 GHz |
| Cluster 2 | 3 Cores @ 3.20 GHz |
| Cluster 3 | 1 Core @ 3.35 GHz |
| Memory Information | |
|---|---|
| Size | 11.18 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1383
257.1 IPS |
|
|
Image Classification (HP)
|
100% |
1142
212.4 IPS |
|
|
Image Classification (Q)
|
99% |
2372
442.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1461
23.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
1325
21.5 IPS |
|
|
Image Segmentation (Q)
|
98% |
2404
39.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
2571
3.00 IPS |
|
|
Pose Estimation (HP)
|
92% |
5105
6.00 IPS |
|
|
Pose Estimation (Q)
|
96% |
6258
7.33 IPS |
|
|
Object Detection (SP)
|
98% |
1249
99.4 IPS |
|
|
Object Detection (HP)
|
97% |
1086
86.5 IPS |
|
|
Object Detection (Q)
|
85% |
2063
166.2 IPS |
|
|
Face Detection (SP)
|
100% |
2567
30.5 IPS |
|
|
Face Detection (HP)
|
100% |
3213
38.2 IPS |
|
|
Face Detection (Q)
|
97% |
5001
59.6 IPS |
|
|
Depth Estimation (SP)
|
99% |
2232
17.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
3736
28.9 IPS |
|
|
Depth Estimation (Q)
|
64% |
4862
44.6 IPS |
|
|
Style Transfer (SP)
|
89% |
6388
8.29 IPS |
|
|
Style Transfer (HP)
|
88% |
6568
8.53 IPS |
|
|
Style Transfer (Q)
|
98% |
13170
17.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1186
43.8 IPS |
|
|
Image Super-Resolution (HP)
|
92% |
2292
85.2 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
3331
123.4 IPS |
|
|
Text Classification (SP)
|
100% |
698
932.3 IPS |
|
|
Text Classification (HP)
|
100% |
1047
1.40 KIPS |
|
|
Text Classification (Q)
|
93% |
1154
1.55 KIPS |
|
|
Machine Translation (SP)
|
100% |
1362
23.5 IPS |
|
|
Machine Translation (HP)
|
96% |
1286
22.2 IPS |
|
|
Machine Translation (Q)
|
55% |
893
24.0 IPS |
