iPhone 15 Pro Max
Geekbench AI Score
3861
Single Precision Score
25334
Half Precision Score
35545
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | May 09 2025 11:37 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4.1 |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1691
314.4 IPS |
|
|
Image Classification (HP)
|
100% |
11878
2.21 KIPS |
|
|
Image Classification (Q)
|
97% |
17188
3.21 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1571
25.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
16465
266.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
21050
341.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
7723
9.01 IPS |
|
|
Pose Estimation (HP)
|
100% |
106798
124.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
204966
240.2 IPS |
|
|
Object Detection (SP)
|
100% |
1757
139.4 IPS |
|
|
Object Detection (HP)
|
100% |
13702
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18714
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3073
36.5 IPS |
|
|
Face Detection (HP)
|
100% |
33887
402.7 IPS |
|
|
Face Detection (Q)
|
100% |
52914
628.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6815
52.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
77917
600.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
126077
985.7 IPS |
|
|
Style Transfer (SP)
|
100% |
20781
26.7 IPS |
|
|
Style Transfer (HP)
|
100% |
205468
264.1 IPS |
|
|
Style Transfer (Q)
|
96% |
253030
326.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4704
173.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33445
1.23 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55053
2.03 KIPS |
|
|
Text Classification (SP)
|
100% |
3161
4.22 KIPS |
|
|
Text Classification (HP)
|
100% |
3178
4.24 KIPS |
|
|
Text Classification (Q)
|
93% |
3288
4.41 KIPS |
|
|
Machine Translation (SP)
|
100% |
3158
54.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6600
113.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7594
131.2 IPS |
