iPhone 15 Pro Max
Geekbench AI Score
3782
Single Precision Score
25288
Half Precision Score
35118
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | October 13 2025 06:36 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0.1 |
| 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% |
1587
295.1 IPS |
|
|
Image Classification (HP)
|
100% |
10684
1.99 KIPS |
|
|
Image Classification (Q)
|
97% |
14605
2.73 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1545
25.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
16067
260.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
21144
342.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
7434
8.67 IPS |
|
|
Pose Estimation (HP)
|
100% |
105279
122.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
201167
235.8 IPS |
|
|
Object Detection (SP)
|
100% |
1667
132.2 IPS |
|
|
Object Detection (HP)
|
100% |
12416
984.9 IPS |
|
|
Object Detection (Q)
|
91% |
16519
1.32 KIPS |
|
|
Face Detection (SP)
|
100% |
3072
36.5 IPS |
|
|
Face Detection (HP)
|
100% |
33979
403.7 IPS |
|
|
Face Detection (Q)
|
100% |
50807
603.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6750
52.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
72078
555.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
111560
872.2 IPS |
|
|
Style Transfer (SP)
|
100% |
20636
26.5 IPS |
|
|
Style Transfer (HP)
|
100% |
200974
258.4 IPS |
|
|
Style Transfer (Q)
|
96% |
242522
313.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4540
167.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
29692
1.10 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56774
2.10 KIPS |
|
|
Text Classification (SP)
|
100% |
3244
4.33 KIPS |
|
|
Text Classification (HP)
|
99% |
5573
7.44 KIPS |
|
|
Text Classification (Q)
|
93% |
5510
7.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
3128
53.9 IPS |
|
|
Machine Translation (HP)
|
100% |
5853
100.8 IPS |
|
|
Machine Translation (Q)
|
98% |
6467
111.8 IPS |
