iPhone 14 Pro Max
Geekbench ML Score
3455
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | September 02 2024 09:24 PM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone 14 Pro Max |
| Model ID | iPhone15,3 |
| Motherboard | D74AP |
| CPU Information | |
|---|---|
| Name | Apple A16 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.46 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 | 5.48 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1394
260.8 IPS |
|
|
Image Classification (F16)
|
100% |
1802
337.2 IPS |
|
|
Image Classification (I8)
|
99% |
1810
338.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
762
12.7 IPS |
|
|
Image Segmentation (F16)
|
100% |
771
12.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
767
12.8 IPS |
|
|
Pose Estimation (F32)
|
100% |
6010
7.28 IPS |
|
|
Pose Estimation (F16)
|
100% |
13634
16.5 IPS |
|
|
Pose Estimation (I8)
|
100% |
13661
16.5 IPS |
|
|
Object Detection (F32)
|
100% |
1404
104.8 IPS |
|
|
Object Detection (F16)
|
100% |
1916
143.0 IPS |
|
|
Object Detection (I8)
|
97% |
1397
104.3 IPS |
|
|
Face Detection (F32)
|
100% |
2648
31.5 IPS |
|
|
Face Detection (F16)
|
97% |
4264
50.7 IPS |
|
|
Face Detection (I8)
|
97% |
4260
50.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
5384
41.8 IPS |
|
|
Depth Estimation (F16)
|
100% |
8345
64.7 IPS |
|
|
Depth Estimation (I8)
|
99% |
8325
64.6 IPS |
|
|
Style Transfer (F32)
|
100% |
16733
22.0 IPS |
|
|
Style Transfer (F16)
|
100% |
25571
33.6 IPS |
|
|
Style Transfer (I8)
|
100% |
25517
33.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3964
141.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4980
177.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5001
178.6 IPS |
|
|
Text Classification (F32)
|
100% |
2377
3.42 KIPS |
|
|
Text Classification (F16)
|
100% |
4045
5.81 KIPS |
|
|
Text Classification (I8)
|
96% |
4005
5.76 KIPS |
|
|
Machine Translation (F32)
|
100% |
1245
22.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1471
27.1 IPS |
|
|
Machine Translation (I8)
|
99% |
1210
22.3 IPS |
