iPhone 15 Pro Max
Geekbench AI Score
3594
Single Precision Score
6640
Half Precision Score
5442
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | May 11 2025 02:42 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4.1 |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1435
266.9 IPS |
|
|
Image Classification (HP)
|
100% |
2831
526.5 IPS |
|
|
Image Classification (Q)
|
96% |
1996
372.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1359
22.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
2318
37.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
2751
44.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
6133
7.16 IPS |
|
|
Pose Estimation (HP)
|
100% |
13826
16.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
12632
14.8 IPS |
|
|
Object Detection (SP)
|
100% |
1671
132.6 IPS |
|
|
Object Detection (HP)
|
97% |
3273
260.5 IPS |
|
|
Object Detection (Q)
|
94% |
2283
182.0 IPS |
|
|
Face Detection (SP)
|
100% |
2995
35.6 IPS |
|
|
Face Detection (HP)
|
100% |
6628
78.8 IPS |
|
|
Face Detection (Q)
|
100% |
3662
43.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6554
50.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
12603
97.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
8776
68.6 IPS |
|
|
Style Transfer (SP)
|
100% |
19977
25.7 IPS |
|
|
Style Transfer (HP)
|
100% |
31596
40.6 IPS |
|
|
Style Transfer (Q)
|
96% |
26533
34.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4578
169.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5610
207.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4353
160.7 IPS |
|
|
Text Classification (SP)
|
100% |
3249
4.34 KIPS |
|
|
Text Classification (HP)
|
100% |
5647
7.54 KIPS |
|
|
Text Classification (Q)
|
93% |
5692
7.64 KIPS |
|
|
Machine Translation (SP)
|
100% |
3086
53.2 IPS |
|
|
Machine Translation (HP)
|
98% |
6716
116.0 IPS |
|
|
Machine Translation (Q)
|
98% |
6817
117.8 IPS |
