iPhone 12
Geekbench ML Score
1402
Core ML GPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | August 17 2024 06:43 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.1 |
| Model | iPhone 12 |
| Model ID | iPhone13,2 |
| Motherboard | D53gAP |
| CPU Information | |
|---|---|
| Name | Apple A14 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 2.99 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 3.58 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
398
74.4 IPS |
|
|
Image Classification (F16)
|
100% |
380
71.0 IPS |
|
|
Image Classification (I8)
|
99% |
380
71.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
325
5.43 IPS |
|
|
Image Segmentation (F16)
|
100% |
323
5.39 IPS |
|
|
Image Segmentation (I8)
|
100% |
321
5.36 IPS |
|
|
Pose Estimation (F32)
|
100% |
6180
7.48 IPS |
|
|
Pose Estimation (F16)
|
100% |
6403
7.75 IPS |
|
|
Pose Estimation (I8)
|
100% |
6155
7.45 IPS |
|
|
Object Detection (F32)
|
100% |
572
42.7 IPS |
|
|
Object Detection (F16)
|
100% |
479
35.8 IPS |
|
|
Object Detection (I8)
|
97% |
647
48.3 IPS |
|
|
Face Detection (F32)
|
100% |
3229
38.4 IPS |
|
|
Face Detection (F16)
|
97% |
3553
42.2 IPS |
|
|
Face Detection (I8)
|
96% |
3571
42.5 IPS |
|
|
Depth Estimation (F32)
|
100% |
5219
40.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
5486
42.5 IPS |
|
|
Depth Estimation (I8)
|
99% |
5549
43.0 IPS |
|
|
Style Transfer (F32)
|
100% |
11050
14.5 IPS |
|
|
Style Transfer (F16)
|
100% |
12269
16.1 IPS |
|
|
Style Transfer (I8)
|
100% |
13329
17.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2008
71.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1877
67.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1971
70.4 IPS |
|
|
Text Classification (F32)
|
100% |
284
407.5 IPS |
|
|
Text Classification (F16)
|
100% |
318
456.7 IPS |
|
|
Text Classification (I8)
|
96% |
313
450.3 IPS |
|
|
Machine Translation (F32)
|
100% |
503
9.26 IPS |
|
|
Machine Translation (F16)
|
100% |
504
9.27 IPS |
|
|
Machine Translation (I8)
|
99% |
491
9.03 IPS |
