iPhone 15 Pro Max
Geekbench AI Score
3798
Single Precision Score
25446
Half Precision Score
34375
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 21 2025 01:56 AM |
| 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% |
1584
294.6 IPS |
|
|
Image Classification (HP)
|
100% |
11503
2.14 KIPS |
|
|
Image Classification (Q)
|
97% |
13444
2.51 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1555
25.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
16275
263.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
21581
349.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
7498
8.75 IPS |
|
|
Pose Estimation (HP)
|
100% |
104982
122.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
199531
233.9 IPS |
|
|
Object Detection (SP)
|
100% |
1666
132.1 IPS |
|
|
Object Detection (HP)
|
100% |
11842
939.3 IPS |
|
|
Object Detection (Q)
|
91% |
15855
1.27 KIPS |
|
|
Face Detection (SP)
|
100% |
3055
36.3 IPS |
|
|
Face Detection (HP)
|
100% |
33826
401.9 IPS |
|
|
Face Detection (Q)
|
100% |
50808
603.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6833
52.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
71037
547.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
110575
864.5 IPS |
|
|
Style Transfer (SP)
|
100% |
20784
26.7 IPS |
|
|
Style Transfer (HP)
|
100% |
201110
258.5 IPS |
|
|
Style Transfer (Q)
|
96% |
238817
308.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4609
170.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
31300
1.16 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
54667
2.02 KIPS |
|
|
Text Classification (SP)
|
100% |
3298
4.40 KIPS |
|
|
Text Classification (HP)
|
99% |
5598
7.47 KIPS |
|
|
Text Classification (Q)
|
93% |
5348
7.18 KIPS |
|
|
Machine Translation (SP)
|
100% |
3080
53.1 IPS |
|
|
Machine Translation (HP)
|
100% |
5777
99.5 IPS |
|
|
Machine Translation (Q)
|
98% |
6399
110.6 IPS |
