iPhone 16 Pro Max
Geekbench AI Score
4428
Single Precision Score
7633
Half Precision Score
6067
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | 3nigma |
| Upload Date | December 19 2024 11:43 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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% |
2002
372.4 IPS |
|
|
Image Classification (HP)
|
100% |
3399
632.2 IPS |
|
|
Image Classification (Q)
|
96% |
2284
426.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1898
30.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2931
47.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
3362
54.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8490
9.91 IPS |
|
|
Pose Estimation (HP)
|
100% |
17456
20.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
14887
17.4 IPS |
|
|
Object Detection (SP)
|
100% |
2098
166.4 IPS |
|
|
Object Detection (HP)
|
97% |
3746
298.2 IPS |
|
|
Object Detection (Q)
|
94% |
2623
209.1 IPS |
|
|
Face Detection (SP)
|
100% |
3507
41.7 IPS |
|
|
Face Detection (HP)
|
100% |
7279
86.5 IPS |
|
|
Face Detection (Q)
|
100% |
4121
49.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
7450
57.4 IPS |
|
|
Depth Estimation (HP)
|
97% |
13963
107.9 IPS |
|
|
Depth Estimation (Q)
|
86% |
9540
74.5 IPS |
|
|
Style Transfer (SP)
|
100% |
23084
29.7 IPS |
|
|
Style Transfer (HP)
|
100% |
36233
46.6 IPS |
|
|
Style Transfer (Q)
|
96% |
29673
38.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5403
199.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6827
252.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4783
176.6 IPS |
|
|
Text Classification (SP)
|
100% |
3478
4.64 KIPS |
|
|
Text Classification (HP)
|
100% |
5866
7.83 KIPS |
|
|
Text Classification (Q)
|
93% |
5823
7.82 KIPS |
|
|
Machine Translation (SP)
|
100% |
3778
65.1 IPS |
|
|
Machine Translation (HP)
|
98% |
6994
120.8 IPS |
|
|
Machine Translation (Q)
|
98% |
6937
119.9 IPS |
