iPhone 15 Pro Max
Geekbench AI Score
3642
Single Precision Score
6636
Half Precision Score
5395
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| Upload Date | August 21 2025 02:47 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| 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% |
1529
284.3 IPS |
|
|
Image Classification (HP)
|
100% |
2955
549.6 IPS |
|
|
Image Classification (Q)
|
96% |
1988
371.3 IPS |
|
|
Image Segmentation (SP)
|
100% |
1508
24.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2260
36.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
2831
45.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
6879
8.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
14234
16.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
12622
14.8 IPS |
|
|
Object Detection (SP)
|
100% |
1649
130.8 IPS |
|
|
Object Detection (HP)
|
97% |
3155
251.2 IPS |
|
|
Object Detection (Q)
|
94% |
2234
178.1 IPS |
|
|
Face Detection (SP)
|
100% |
2895
34.4 IPS |
|
|
Face Detection (HP)
|
100% |
6346
75.4 IPS |
|
|
Face Detection (Q)
|
100% |
3558
42.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6392
49.2 IPS |
|
|
Depth Estimation (HP)
|
98% |
12180
94.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
8507
66.5 IPS |
|
|
Style Transfer (SP)
|
100% |
19099
24.6 IPS |
|
|
Style Transfer (HP)
|
100% |
31585
40.6 IPS |
|
|
Style Transfer (Q)
|
96% |
26004
33.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4297
158.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5609
207.1 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4173
154.1 IPS |
|
|
Text Classification (SP)
|
100% |
3273
4.37 KIPS |
|
|
Text Classification (HP)
|
99% |
5685
7.59 KIPS |
|
|
Text Classification (Q)
|
93% |
5646
7.58 KIPS |
|
|
Machine Translation (SP)
|
100% |
3165
54.5 IPS |
|
|
Machine Translation (HP)
|
98% |
7101
122.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7103
122.7 IPS |
