iPhone 14
Geekbench ML Score
1924
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 16 2024 02:34 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.3.1 |
| Model | iPhone 14 |
| Model ID | iPhone14,7 |
| Motherboard | D27AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 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 | 5.56 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
948
177.4 IPS |
|
|
Image Classification (F16)
|
100% |
904
169.1 IPS |
|
|
Image Classification (I8)
|
99% |
903
169.0 IPS |
|
|
Image Segmentation (F32)
|
100% |
636
10.6 IPS |
|
|
Image Segmentation (F16)
|
100% |
572
9.56 IPS |
|
|
Image Segmentation (I8)
|
100% |
568
9.48 IPS |
|
|
Pose Estimation (F32)
|
100% |
5472
6.63 IPS |
|
|
Pose Estimation (F16)
|
100% |
9537
11.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
9596
11.6 IPS |
|
|
Object Detection (F32)
|
100% |
1033
77.1 IPS |
|
|
Object Detection (F16)
|
100% |
1045
78.0 IPS |
|
|
Object Detection (I8)
|
97% |
1031
77.0 IPS |
|
|
Face Detection (F32)
|
100% |
1739
20.7 IPS |
|
|
Face Detection (F16)
|
100% |
1607
19.1 IPS |
|
|
Face Detection (I8)
|
99% |
1583
18.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
3250
25.2 IPS |
|
|
Depth Estimation (F16)
|
99% |
3651
28.3 IPS |
|
|
Depth Estimation (I8)
|
99% |
3633
28.2 IPS |
|
|
Style Transfer (F32)
|
100% |
9769
12.9 IPS |
|
|
Style Transfer (F16)
|
100% |
11692
15.4 IPS |
|
|
Style Transfer (I8)
|
100% |
11755
15.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2429
86.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
2564
91.6 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
2561
91.5 IPS |
|
|
Text Classification (F32)
|
100% |
1006
1.45 KIPS |
|
|
Text Classification (F16)
|
100% |
467
670.6 IPS |
|
|
Text Classification (I8)
|
96% |
623
895.2 IPS |
|
|
Machine Translation (F32)
|
100% |
1348
24.8 IPS |
|
|
Machine Translation (F16)
|
99% |
1766
32.5 IPS |
|
|
Machine Translation (I8)
|
99% |
1338
24.6 IPS |
