iPhone 16 Pro Max
Geekbench AI Score
4412
Single Precision Score
7596
Half Precision Score
6032
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | Farzad |
| Upload Date | February 19 2025 10:07 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.3.1 |
| Model | iPhone 16 Pro Max |
| Model ID | iPhone17,2 |
| Motherboard | D94AP |
| CPU Information | |
|---|---|
| Name | Apple A18 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.45 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2010
373.9 IPS |
|
|
Image Classification (HP)
|
100% |
3373
627.4 IPS |
|
|
Image Classification (Q)
|
96% |
2268
423.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1892
30.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2877
46.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
3358
54.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
8611
10.0 IPS |
|
|
Pose Estimation (HP)
|
100% |
17390
20.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
14565
17.1 IPS |
|
|
Object Detection (SP)
|
100% |
2077
164.8 IPS |
|
|
Object Detection (HP)
|
97% |
3761
299.4 IPS |
|
|
Object Detection (Q)
|
94% |
2611
208.1 IPS |
|
|
Face Detection (SP)
|
100% |
3495
41.5 IPS |
|
|
Face Detection (HP)
|
100% |
7241
86.0 IPS |
|
|
Face Detection (Q)
|
100% |
4065
48.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7483
57.7 IPS |
|
|
Depth Estimation (HP)
|
97% |
13486
104.3 IPS |
|
|
Depth Estimation (Q)
|
86% |
9433
73.6 IPS |
|
|
Style Transfer (SP)
|
100% |
23113
29.7 IPS |
|
|
Style Transfer (HP)
|
100% |
36457
46.9 IPS |
|
|
Style Transfer (Q)
|
96% |
29491
38.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5398
199.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6852
253.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4833
178.5 IPS |
|
|
Text Classification (SP)
|
100% |
3423
4.57 KIPS |
|
|
Text Classification (HP)
|
100% |
5922
7.90 KIPS |
|
|
Text Classification (Q)
|
93% |
5855
7.86 KIPS |
|
|
Machine Translation (SP)
|
100% |
3680
63.4 IPS |
|
|
Machine Translation (HP)
|
98% |
6979
120.6 IPS |
|
|
Machine Translation (Q)
|
98% |
6890
119.1 IPS |
