iPhone 15 Pro Max
Geekbench AI Score
2573
Single Precision Score
14028
Half Precision Score
15864
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | macprime |
| Upload Date | August 15 2024 08:21 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| Model | iPhone 15 Pro Max |
| Model ID | iPhone16,2 |
| Motherboard | D84AP |
| CPU Information | |
|---|---|
| Name | Apple A17 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.78 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1321
245.7 IPS |
|
|
Image Classification (HP)
|
100% |
6257
1.16 KIPS |
|
|
Image Classification (Q)
|
99% |
6901
1.29 KIPS |
|
|
Image Segmentation (SP)
|
100% |
746
12.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
5252
85.1 IPS |
|
|
Image Segmentation (Q)
|
100% |
5132
83.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6240
7.28 IPS |
|
|
Pose Estimation (HP)
|
100% |
86757
101.2 IPS |
|
|
Pose Estimation (Q)
|
94% |
131557
154.3 IPS |
|
|
Object Detection (SP)
|
100% |
1457
115.6 IPS |
|
|
Object Detection (HP)
|
100% |
8201
650.5 IPS |
|
|
Object Detection (Q)
|
93% |
9198
734.0 IPS |
|
|
Face Detection (SP)
|
100% |
2101
25.0 IPS |
|
|
Face Detection (HP)
|
100% |
11165
132.7 IPS |
|
|
Face Detection (Q)
|
100% |
12628
150.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
4543
35.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
43329
333.8 IPS |
|
|
Depth Estimation (Q)
|
97% |
47912
370.5 IPS |
|
|
Style Transfer (SP)
|
100% |
12008
15.4 IPS |
|
|
Style Transfer (HP)
|
100% |
128113
164.7 IPS |
|
|
Style Transfer (Q)
|
100% |
128193
164.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3748
138.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18361
678.0 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
26830
994.0 IPS |
|
|
Text Classification (SP)
|
100% |
1779
2.37 KIPS |
|
|
Text Classification (HP)
|
71% |
4590
6.60 KIPS |
|
|
Text Classification (Q)
|
69% |
4699
6.89 KIPS |
|
|
Machine Translation (SP)
|
100% |
1864
32.1 IPS |
|
|
Machine Translation (HP)
|
100% |
2418
41.7 IPS |
|
|
Machine Translation (Q)
|
98% |
2410
41.7 IPS |
