iPhone 14 Pro Max
Geekbench ML Score
3537
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | May 09 2024 11:13 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 17.4.1 |
| 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% |
1442
269.8 IPS |
|
|
Image Classification (F16)
|
100% |
1867
349.4 IPS |
|
|
Image Classification (I8)
|
99% |
1873
350.5 IPS |
|
|
Image Segmentation (F32)
|
100% |
768
12.8 IPS |
|
|
Image Segmentation (F16)
|
100% |
773
12.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
775
12.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
6338
7.67 IPS |
|
|
Pose Estimation (F16)
|
100% |
14249
17.3 IPS |
|
|
Pose Estimation (I8)
|
100% |
14231
17.2 IPS |
|
|
Object Detection (F32)
|
100% |
1436
107.2 IPS |
|
|
Object Detection (F16)
|
100% |
2002
149.4 IPS |
|
|
Object Detection (I8)
|
97% |
1445
107.9 IPS |
|
|
Face Detection (F32)
|
100% |
2733
32.5 IPS |
|
|
Face Detection (F16)
|
97% |
4390
52.2 IPS |
|
|
Face Detection (I8)
|
97% |
4393
52.2 IPS |
|
|
Depth Estimation (F32)
|
100% |
5574
43.2 IPS |
|
|
Depth Estimation (F16)
|
100% |
8661
67.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
8651
67.1 IPS |
|
|
Style Transfer (F32)
|
100% |
17350
22.8 IPS |
|
|
Style Transfer (F16)
|
100% |
26437
34.8 IPS |
|
|
Style Transfer (I8)
|
100% |
26417
34.7 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
4020
143.6 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4970
177.5 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
5063
180.8 IPS |
|
|
Text Classification (F32)
|
100% |
2382
3.42 KIPS |
|
|
Text Classification (F16)
|
100% |
3920
5.63 KIPS |
|
|
Text Classification (I8)
|
96% |
4086
5.87 KIPS |
|
|
Machine Translation (F32)
|
100% |
1225
22.5 IPS |
|
|
Machine Translation (F16)
|
100% |
1521
28.0 IPS |
|
|
Machine Translation (I8)
|
99% |
1214
22.3 IPS |
