alps M2C-300
Geekbench AI Score
16
Single Precision Score
206
Half Precision Score
161
Quantized Score
Geekbench AI 1.5.0 for Android AArch64
Result Information
| Upload Date | September 16 2025 03:26 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | TensorFlow Lite |
| Backend | GPU |
| Device | ARM ARMv8 |
| System Information | |
|---|---|
| Operating System | Android 13 |
| Model | alps M2C-300 |
| Model ID | alps M2C-300 |
| Motherboard | an300t |
| Governor | schedutil |
| CPU Information | |
|---|---|
| Name | ARM ARMv8 |
| Topology | 1 Processor, 4 Cores |
| Identifier | ARM implementer 65 architecture 8 variant 0 part 3331 revision 4 |
| Base Frequency | 2.00 GHz |
| Cluster 1 | 4 Cores @ 2.00 GHz |
| Memory Information | |
|---|---|
| Size | 2.80 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
0% |
0
11.7 IPS |
|
|
Image Classification (HP)
|
100% |
121
22.6 IPS |
|
|
Image Classification (Q)
|
97% |
111
20.7 IPS |
|
|
Image Segmentation (SP)
|
73% |
82
1.41 IPS |
|
|
Image Segmentation (HP)
|
100% |
180
2.92 IPS |
|
|
Image Segmentation (Q)
|
98% |
163
2.66 IPS |
|
|
Pose Estimation (SP)
|
100% |
351
0.41 IPS |
|
|
Pose Estimation (HP)
|
100% |
695
0.81 IPS |
|
|
Pose Estimation (Q)
|
95% |
682
0.80 IPS |
|
|
Object Detection (SP)
|
1% |
0
4.73 IPS |
|
|
Object Detection (HP)
|
99% |
122
9.70 IPS |
|
|
Object Detection (Q)
|
83% |
114
9.20 IPS |
|
|
Face Detection (SP)
|
0% |
0
2.72 IPS |
|
|
Face Detection (HP)
|
100% |
458
5.44 IPS |
|
|
Face Detection (Q)
|
96% |
395
4.71 IPS |
|
|
Depth Estimation (SP)
|
1% |
1
1.73 IPS |
|
|
Depth Estimation (HP)
|
98% |
443
3.42 IPS |
|
|
Depth Estimation (Q)
|
62% |
347
3.30 IPS |
|
|
Style Transfer (SP)
|
100% |
539
0.69 IPS |
|
|
Style Transfer (HP)
|
100% |
1117
1.44 IPS |
|
|
Style Transfer (Q)
|
98% |
1102
1.42 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
163
6.02 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
289
10.7 IPS |
|
|
Image Super-Resolution (Q)
|
97% |
283
10.5 IPS |
|
|
Text Classification (SP)
|
35% |
5
50.0 IPS |
|
|
Text Classification (HP)
|
35% |
7
70.6 IPS |
|
|
Text Classification (Q)
|
32% |
5
69.1 IPS |
|
|
Machine Translation (SP)
|
100% |
108
1.86 IPS |
|
|
Machine Translation (HP)
|
100% |
164
2.83 IPS |
|
|
Machine Translation (Q)
|
43% |
39
2.27 IPS |
