iPhone 15 Pro Max
Geekbench AI Score
3831
Single Precision Score
26787
Half Precision Score
36155
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 22 2025 09:18 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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 | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1558
289.7 IPS |
|
|
Image Classification (HP)
|
100% |
11663
2.17 KIPS |
|
|
Image Classification (Q)
|
97% |
14331
2.67 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1554
25.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
16454
266.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
21243
344.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7702
8.99 IPS |
|
|
Pose Estimation (HP)
|
100% |
107213
125.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
206318
241.8 IPS |
|
|
Object Detection (SP)
|
100% |
1668
132.3 IPS |
|
|
Object Detection (HP)
|
100% |
14008
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
18141
1.45 KIPS |
|
|
Face Detection (SP)
|
100% |
3095
36.8 IPS |
|
|
Face Detection (HP)
|
100% |
33719
400.7 IPS |
|
|
Face Detection (Q)
|
100% |
50509
600.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6965
53.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
78423
604.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
127145
994.1 IPS |
|
|
Style Transfer (SP)
|
100% |
21395
27.5 IPS |
|
|
Style Transfer (HP)
|
100% |
204701
263.1 IPS |
|
|
Style Transfer (Q)
|
96% |
253363
327.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4708
173.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34842
1.29 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
53824
1.99 KIPS |
|
|
Text Classification (SP)
|
100% |
3242
4.33 KIPS |
|
|
Text Classification (HP)
|
99% |
5392
7.20 KIPS |
|
|
Text Classification (Q)
|
93% |
5385
7.23 KIPS |
|
|
Machine Translation (SP)
|
100% |
3112
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6491
111.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7104
122.8 IPS |
