iPhone 13 Pro Max
Geekbench ML Score
5458
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | January 23 2024 11:50 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.6.1 |
| Model | iPhone 13 Pro Max |
| Model ID | iPhone14,3 |
| Motherboard | D64AP |
| 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 | 5.49 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1690
316.2 IPS |
|
|
Image Classification (F16)
|
100% |
5759
1.08 KIPS |
|
|
Image Classification (I8)
|
99% |
5612
1.05 KIPS |
|
|
Image Segmentation (F32)
|
100% |
629
10.5 IPS |
|
|
Image Segmentation (F16)
|
100% |
2959
49.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
2905
48.5 IPS |
|
|
Pose Estimation (F32)
|
100% |
11099
13.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
75684
91.6 IPS |
|
|
Pose Estimation (I8)
|
100% |
74595
90.3 IPS |
|
|
Object Detection (F32)
|
100% |
1895
141.4 IPS |
|
|
Object Detection (F16)
|
100% |
3387
252.8 IPS |
|
|
Object Detection (I8)
|
97% |
1430
106.8 IPS |
|
|
Face Detection (F32)
|
100% |
4565
54.3 IPS |
|
|
Face Detection (F16)
|
97% |
9588
114.0 IPS |
|
|
Face Detection (I8)
|
96% |
10151
120.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
8646
67.1 IPS |
|
|
Depth Estimation (F16)
|
100% |
25324
196.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
26130
202.6 IPS |
|
|
Style Transfer (F32)
|
100% |
18835
24.8 IPS |
|
|
Style Transfer (F16)
|
100% |
90188
118.6 IPS |
|
|
Style Transfer (I8)
|
100% |
90715
119.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5090
181.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11430
408.2 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
11835
422.7 IPS |
|
|
Text Classification (F32)
|
100% |
422
605.9 IPS |
|
|
Text Classification (F16)
|
100% |
841
1.21 KIPS |
|
|
Text Classification (I8)
|
96% |
863
1.24 KIPS |
|
|
Machine Translation (F32)
|
100% |
920
16.9 IPS |
|
|
Machine Translation (F16)
|
100% |
1132
20.8 IPS |
|
|
Machine Translation (I8)
|
99% |
885
16.3 IPS |
