iPhone 15 Pro Max
Geekbench AI Score
4013
Single Precision Score
24862
Half Precision Score
34748
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 29 2024 12:49 AM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.3 |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1684
313.2 IPS |
|
|
Image Classification (HP)
|
100% |
11028
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
15685
2.93 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1671
27.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
15713
254.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
20738
336.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
8459
9.87 IPS |
|
|
Pose Estimation (HP)
|
100% |
106160
123.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
201932
236.7 IPS |
|
|
Object Detection (SP)
|
100% |
1823
144.6 IPS |
|
|
Object Detection (HP)
|
100% |
13732
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18455
1.47 KIPS |
|
|
Face Detection (SP)
|
100% |
3146
37.4 IPS |
|
|
Face Detection (HP)
|
100% |
33741
400.9 IPS |
|
|
Face Detection (Q)
|
100% |
49961
593.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7184
55.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
78297
603.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
126924
992.3 IPS |
|
|
Style Transfer (SP)
|
100% |
22047
28.3 IPS |
|
|
Style Transfer (HP)
|
100% |
204800
263.3 IPS |
|
|
Style Transfer (Q)
|
96% |
249299
321.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5168
190.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
36121
1.33 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57500
2.12 KIPS |
|
|
Text Classification (SP)
|
100% |
3125
4.17 KIPS |
|
|
Text Classification (HP)
|
100% |
2999
4.00 KIPS |
|
|
Text Classification (Q)
|
93% |
3113
4.18 KIPS |
|
|
Machine Translation (SP)
|
100% |
3107
53.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6096
105.0 IPS |
|
|
Machine Translation (Q)
|
98% |
7482
129.3 IPS |
