iPhone 15 Pro Max
Geekbench AI Score
2756
Single Precision Score
14061
Half Precision Score
15784
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | DFW |
| Upload Date | September 02 2024 06:28 PM |
| Views | 3 |
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% |
1431
266.1 IPS |
|
|
Image Classification (HP)
|
100% |
6488
1.21 KIPS |
|
|
Image Classification (Q)
|
99% |
6778
1.26 KIPS |
|
|
Image Segmentation (SP)
|
100% |
824
13.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
5249
85.1 IPS |
|
|
Image Segmentation (Q)
|
100% |
5193
84.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7945
9.27 IPS |
|
|
Pose Estimation (HP)
|
100% |
87899
102.6 IPS |
|
|
Pose Estimation (Q)
|
94% |
138451
162.4 IPS |
|
|
Object Detection (SP)
|
100% |
1458
115.6 IPS |
|
|
Object Detection (HP)
|
100% |
8148
646.3 IPS |
|
|
Object Detection (Q)
|
93% |
9935
792.7 IPS |
|
|
Face Detection (SP)
|
100% |
2217
26.3 IPS |
|
|
Face Detection (HP)
|
100% |
11175
132.8 IPS |
|
|
Face Detection (Q)
|
100% |
12524
148.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
4677
36.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
47633
367.0 IPS |
|
|
Depth Estimation (Q)
|
97% |
47990
371.1 IPS |
|
|
Style Transfer (SP)
|
100% |
12498
16.1 IPS |
|
|
Style Transfer (HP)
|
100% |
127873
164.4 IPS |
|
|
Style Transfer (Q)
|
100% |
128295
164.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4023
148.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18462
681.7 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
26109
967.3 IPS |
|
|
Text Classification (SP)
|
100% |
1841
2.46 KIPS |
|
|
Text Classification (HP)
|
71% |
4079
5.86 KIPS |
|
|
Text Classification (Q)
|
69% |
4090
6.00 KIPS |
|
|
Machine Translation (SP)
|
100% |
1931
33.3 IPS |
|
|
Machine Translation (HP)
|
100% |
2417
41.6 IPS |
|
|
Machine Translation (Q)
|
98% |
2409
41.6 IPS |
