iPhone 15 Pro Max
Geekbench AI Score
3785
Single Precision Score
26411
Half Precision Score
36657
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 21 2025 06:50 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% |
1575
292.9 IPS |
|
|
Image Classification (HP)
|
100% |
10791
2.01 KIPS |
|
|
Image Classification (Q)
|
97% |
15260
2.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1556
25.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
16592
269.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
21098
342.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7226
8.43 IPS |
|
|
Pose Estimation (HP)
|
100% |
105382
123.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
205743
241.1 IPS |
|
|
Object Detection (SP)
|
100% |
1661
131.8 IPS |
|
|
Object Detection (HP)
|
100% |
13827
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
17742
1.42 KIPS |
|
|
Face Detection (SP)
|
100% |
3056
36.3 IPS |
|
|
Face Detection (HP)
|
100% |
33974
403.7 IPS |
|
|
Face Detection (Q)
|
100% |
50855
604.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6790
52.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
77846
599.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
127075
993.5 IPS |
|
|
Style Transfer (SP)
|
100% |
20709
26.6 IPS |
|
|
Style Transfer (HP)
|
100% |
205658
264.4 IPS |
|
|
Style Transfer (Q)
|
96% |
249720
322.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4672
172.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34333
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
60945
2.25 KIPS |
|
|
Text Classification (SP)
|
100% |
3271
4.37 KIPS |
|
|
Text Classification (HP)
|
99% |
5386
7.19 KIPS |
|
|
Text Classification (Q)
|
93% |
5432
7.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
3125
53.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6294
108.4 IPS |
|
|
Machine Translation (Q)
|
98% |
6978
120.6 IPS |
