iPhone 15 Pro Max
Geekbench AI Score
3897
Single Precision Score
6900
Half Precision Score
5638
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | June 03 2025 07:50 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| 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% |
1691
314.5 IPS |
|
|
Image Classification (HP)
|
100% |
2967
551.8 IPS |
|
|
Image Classification (Q)
|
96% |
2036
380.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1592
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2337
37.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
3028
49.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7943
9.27 IPS |
|
|
Pose Estimation (HP)
|
100% |
16399
19.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
14218
16.7 IPS |
|
|
Object Detection (SP)
|
100% |
1766
140.1 IPS |
|
|
Object Detection (HP)
|
97% |
3283
261.4 IPS |
|
|
Object Detection (Q)
|
94% |
2342
186.7 IPS |
|
|
Face Detection (SP)
|
100% |
3085
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
6722
79.9 IPS |
|
|
Face Detection (Q)
|
100% |
3774
44.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6749
52.0 IPS |
|
|
Depth Estimation (HP)
|
98% |
12943
100.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
8925
69.8 IPS |
|
|
Style Transfer (SP)
|
100% |
20984
27.0 IPS |
|
|
Style Transfer (HP)
|
100% |
33822
43.5 IPS |
|
|
Style Transfer (Q)
|
96% |
27077
34.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4817
177.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5735
211.8 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4452
164.4 IPS |
|
|
Text Classification (SP)
|
100% |
3245
4.33 KIPS |
|
|
Text Classification (HP)
|
100% |
5729
7.65 KIPS |
|
|
Text Classification (Q)
|
93% |
5683
7.63 KIPS |
|
|
Machine Translation (SP)
|
100% |
3134
54.0 IPS |
|
|
Machine Translation (HP)
|
98% |
6787
117.3 IPS |
|
|
Machine Translation (Q)
|
98% |
6859
118.5 IPS |
