FCNT M08
Geekbench AI Score
1336
Single Precision Score
1836
Half Precision Score
1499
Quantized Score
Geekbench AI 1.7.0 for Android AArch64
Result Information
| User | Keitan924111 |
| Upload Date | March 06 2026 05:09 AM |
| Views | 11 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| 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% |
606
112.8 IPS |
|
|
Image Classification (HP)
|
100% |
918
170.8 IPS |
|
|
Image Classification (Q)
|
97% |
775
144.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1673
27.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
2522
40.9 IPS |
|
|
Image Segmentation (Q)
|
98% |
2321
37.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7592
8.86 IPS |
|
|
Pose Estimation (HP)
|
100% |
12485
14.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
11955
14.0 IPS |
|
|
Object Detection (SP)
|
100% |
658
52.2 IPS |
|
|
Object Detection (HP)
|
99% |
985
78.1 IPS |
|
|
Object Detection (Q)
|
83% |
922
74.4 IPS |
|
|
Face Detection (SP)
|
100% |
2437
29.0 IPS |
|
|
Face Detection (HP)
|
100% |
3867
45.9 IPS |
|
|
Face Detection (Q)
|
96% |
3261
38.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
3971
30.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
6452
49.9 IPS |
|
|
Depth Estimation (Q)
|
62% |
5207
49.5 IPS |
|
|
Style Transfer (SP)
|
100% |
12197
15.7 IPS |
|
|
Style Transfer (HP)
|
100% |
21438
27.6 IPS |
|
|
Style Transfer (Q)
|
98% |
20814
26.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
2004
74.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
2889
106.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
2629
97.4 IPS |
|
|
Text Classification (SP)
|
35% |
23
209.5 IPS |
|
|
Text Classification (HP)
|
29% |
14
233.3 IPS |
|
|
Text Classification (Q)
|
32% |
17
224.8 IPS |
|
|
Machine Translation (SP)
|
100% |
659
11.4 IPS |
|
|
Machine Translation (HP)
|
100% |
708
12.2 IPS |
|
|
Machine Translation (Q)
|
43% |
184
10.7 IPS |
