iPhone 14 Pro Max
Geekbench ML Score
871
Core ML CPU Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | October 21 2025 12:39 AM |
| Views | 6 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.2 |
| 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 | 5.49 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
389
72.8 IPS |
|
|
Image Classification (F16)
|
100% |
401
75.0 IPS |
|
|
Image Classification (I8)
|
99% |
402
75.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
296
4.95 IPS |
|
|
Image Segmentation (F16)
|
100% |
256
4.28 IPS |
|
|
Image Segmentation (I8)
|
100% |
257
4.30 IPS |
|
|
Pose Estimation (F32)
|
100% |
2387
2.89 IPS |
|
|
Pose Estimation (F16)
|
100% |
4490
5.44 IPS |
|
|
Pose Estimation (I8)
|
100% |
4496
5.44 IPS |
|
|
Object Detection (F32)
|
100% |
441
32.9 IPS |
|
|
Object Detection (F16)
|
100% |
462
34.5 IPS |
|
|
Object Detection (I8)
|
97% |
452
33.8 IPS |
|
|
Face Detection (F32)
|
100% |
864
10.3 IPS |
|
|
Face Detection (F16)
|
100% |
741
8.81 IPS |
|
|
Face Detection (I8)
|
99% |
740
8.80 IPS |
|
|
Depth Estimation (F32)
|
100% |
1488
11.5 IPS |
|
|
Depth Estimation (F16)
|
99% |
1656
12.8 IPS |
|
|
Depth Estimation (I8)
|
99% |
1661
12.9 IPS |
|
|
Style Transfer (F32)
|
100% |
4461
5.87 IPS |
|
|
Style Transfer (F16)
|
100% |
5279
6.94 IPS |
|
|
Style Transfer (I8)
|
100% |
5291
6.96 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
1043
37.3 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
1171
41.8 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
1165
41.6 IPS |
|
|
Text Classification (F32)
|
100% |
470
675.7 IPS |
|
|
Text Classification (F16)
|
100% |
243
349.1 IPS |
|
|
Text Classification (I8)
|
96% |
289
415.5 IPS |
|
|
Machine Translation (F32)
|
100% |
581
10.7 IPS |
|
|
Machine Translation (F16)
|
99% |
775
14.3 IPS |
|
|
Machine Translation (I8)
|
99% |
577
10.6 IPS |
