iPhone 11
Geekbench ML Score
1112
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 08 2024 03:52 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.0.1 |
| Model | iPhone 11 |
| Model ID | iPhone12,1 |
| Motherboard | N104AP |
| CPU Information | |
|---|---|
| Name | Apple A13 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.66 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 96.0 KB x 1 |
| L1 Data Cache | 48.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.76 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
535
100.2 IPS |
|
|
Image Classification (F16)
|
100% |
639
119.5 IPS |
|
|
Image Classification (I8)
|
99% |
638
119.4 IPS |
|
|
Image Segmentation (F32)
|
100% |
300
5.02 IPS |
|
|
Image Segmentation (F16)
|
100% |
296
4.95 IPS |
|
|
Image Segmentation (I8)
|
100% |
294
4.91 IPS |
|
|
Pose Estimation (F32)
|
100% |
3120
3.78 IPS |
|
|
Pose Estimation (F16)
|
100% |
5531
6.70 IPS |
|
|
Pose Estimation (I8)
|
100% |
5500
6.66 IPS |
|
|
Object Detection (F32)
|
100% |
557
41.6 IPS |
|
|
Object Detection (F16)
|
100% |
716
53.5 IPS |
|
|
Object Detection (I8)
|
97% |
560
41.8 IPS |
|
|
Face Detection (F32)
|
100% |
1127
13.4 IPS |
|
|
Face Detection (F16)
|
100% |
1102
13.1 IPS |
|
|
Face Detection (I8)
|
99% |
1105
13.1 IPS |
|
|
Depth Estimation (F32)
|
100% |
1869
14.5 IPS |
|
|
Depth Estimation (F16)
|
99% |
1930
15.0 IPS |
|
|
Depth Estimation (I8)
|
99% |
2205
17.1 IPS |
|
|
Style Transfer (F32)
|
100% |
5032
6.62 IPS |
|
|
Style Transfer (F16)
|
100% |
7449
9.80 IPS |
|
|
Style Transfer (I8)
|
100% |
7546
9.93 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1665
59.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1675
59.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1681
60.0 IPS |
|
|
Text Classification (F32)
|
100% |
636
914.5 IPS |
|
|
Text Classification (F16)
|
100% |
395
568.0 IPS |
|
|
Text Classification (I8)
|
96% |
400
575.4 IPS |
|
|
Machine Translation (F32)
|
100% |
489
9.01 IPS |
|
|
Machine Translation (F16)
|
99% |
593
10.9 IPS |
|
|
Machine Translation (I8)
|
99% |
478
8.79 IPS |
