iPhone 15 Pro Max
Geekbench AI Score
2636
Single Precision Score
13836
Half Precision Score
15560
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | 3Dman |
| Upload Date | August 25 2024 10:25 AM |
| Views | 17 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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% |
1432
266.4 IPS |
|
|
Image Classification (HP)
|
100% |
6147
1.14 KIPS |
|
|
Image Classification (Q)
|
99% |
6817
1.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
802
13.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
5258
85.2 IPS |
|
|
Image Segmentation (Q)
|
100% |
5192
84.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7448
8.69 IPS |
|
|
Pose Estimation (HP)
|
100% |
88162
102.9 IPS |
|
|
Pose Estimation (Q)
|
94% |
127100
149.1 IPS |
|
|
Object Detection (SP)
|
100% |
1422
112.8 IPS |
|
|
Object Detection (HP)
|
100% |
8208
651.1 IPS |
|
|
Object Detection (Q)
|
93% |
9212
735.0 IPS |
|
|
Face Detection (SP)
|
100% |
2114
25.1 IPS |
|
|
Face Detection (HP)
|
100% |
11119
132.1 IPS |
|
|
Face Detection (Q)
|
100% |
12928
153.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
4398
33.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
42727
329.2 IPS |
|
|
Depth Estimation (Q)
|
97% |
47940
370.7 IPS |
|
|
Style Transfer (SP)
|
100% |
11826
15.2 IPS |
|
|
Style Transfer (HP)
|
100% |
127975
164.5 IPS |
|
|
Style Transfer (Q)
|
100% |
128012
164.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3761
138.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18544
684.7 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
26439
979.5 IPS |
|
|
Text Classification (SP)
|
100% |
1731
2.31 KIPS |
|
|
Text Classification (HP)
|
71% |
3995
5.75 KIPS |
|
|
Text Classification (Q)
|
69% |
3965
5.81 KIPS |
|
|
Machine Translation (SP)
|
100% |
1861
32.1 IPS |
|
|
Machine Translation (HP)
|
100% |
2441
42.0 IPS |
|
|
Machine Translation (Q)
|
98% |
2414
41.7 IPS |
