iPhone 15 Pro Max
Geekbench AI Score
3859
Single Precision Score
6752
Half Precision Score
5533
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | HNT |
| Upload Date | December 17 2024 02:22 AM |
| Views | 12 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| 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% |
1697
315.6 IPS |
|
|
Image Classification (HP)
|
100% |
2904
540.1 IPS |
|
|
Image Classification (Q)
|
96% |
2017
376.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1662
26.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2390
38.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
3077
49.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
7739
9.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
15806
18.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
13717
16.1 IPS |
|
|
Object Detection (SP)
|
100% |
1657
131.4 IPS |
|
|
Object Detection (HP)
|
97% |
3329
265.1 IPS |
|
|
Object Detection (Q)
|
94% |
2334
186.1 IPS |
|
|
Face Detection (SP)
|
100% |
3083
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
6708
79.7 IPS |
|
|
Face Detection (Q)
|
100% |
3820
45.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6751
52.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
13198
102.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
9153
71.6 IPS |
|
|
Style Transfer (SP)
|
100% |
20633
26.5 IPS |
|
|
Style Transfer (HP)
|
100% |
31766
40.8 IPS |
|
|
Style Transfer (Q)
|
96% |
26869
34.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4770
176.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5752
212.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4343
160.4 IPS |
|
|
Text Classification (SP)
|
100% |
3197
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
5522
7.37 KIPS |
|
|
Text Classification (Q)
|
93% |
5509
7.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
3094
53.3 IPS |
|
|
Machine Translation (HP)
|
98% |
6043
104.4 IPS |
|
|
Machine Translation (Q)
|
98% |
6031
104.2 IPS |
