iPhone 15 Pro Max
Geekbench AI Score
3797
Single Precision Score
25933
Half Precision Score
35542
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 06 2025 06:44 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% |
1646
306.1 IPS |
|
|
Image Classification (HP)
|
100% |
11005
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
14386
2.68 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1569
25.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
16510
267.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
21169
343.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7436
8.68 IPS |
|
|
Pose Estimation (HP)
|
100% |
101700
118.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
201044
235.6 IPS |
|
|
Object Detection (SP)
|
100% |
1716
136.1 IPS |
|
|
Object Detection (HP)
|
100% |
13365
1.06 KIPS |
|
|
Object Detection (Q)
|
91% |
17104
1.37 KIPS |
|
|
Face Detection (SP)
|
100% |
3070
36.5 IPS |
|
|
Face Detection (HP)
|
100% |
35502
421.8 IPS |
|
|
Face Detection (Q)
|
100% |
50760
603.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6570
50.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
71622
551.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
113942
890.9 IPS |
|
|
Style Transfer (SP)
|
100% |
19965
25.7 IPS |
|
|
Style Transfer (HP)
|
100% |
203639
261.8 IPS |
|
|
Style Transfer (Q)
|
96% |
240690
310.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4590
169.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
32980
1.22 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55081
2.03 KIPS |
|
|
Text Classification (SP)
|
100% |
3221
4.30 KIPS |
|
|
Text Classification (HP)
|
99% |
5559
7.42 KIPS |
|
|
Text Classification (Q)
|
93% |
5530
7.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
3178
54.7 IPS |
|
|
Machine Translation (HP)
|
100% |
5870
101.1 IPS |
|
|
Machine Translation (Q)
|
98% |
7246
125.2 IPS |
