iPhone 15 Pro Max
Geekbench AI Score
3910
Single Precision Score
6913
Half Precision Score
5671
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 16 2025 06:08 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4 |
| 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% |
1688
314.0 IPS |
|
|
Image Classification (HP)
|
100% |
2973
552.8 IPS |
|
|
Image Classification (Q)
|
96% |
2023
377.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1595
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2350
38.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
3032
49.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
8028
9.37 IPS |
|
|
Pose Estimation (HP)
|
100% |
16536
19.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
14300
16.8 IPS |
|
|
Object Detection (SP)
|
100% |
1769
140.3 IPS |
|
|
Object Detection (HP)
|
97% |
3311
263.6 IPS |
|
|
Object Detection (Q)
|
94% |
2375
189.3 IPS |
|
|
Face Detection (SP)
|
100% |
3086
36.7 IPS |
|
|
Face Detection (HP)
|
100% |
6735
80.0 IPS |
|
|
Face Detection (Q)
|
100% |
3811
45.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6847
52.7 IPS |
|
|
Depth Estimation (HP)
|
98% |
12829
99.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
8958
70.0 IPS |
|
|
Style Transfer (SP)
|
100% |
20784
26.7 IPS |
|
|
Style Transfer (HP)
|
100% |
33348
42.9 IPS |
|
|
Style Transfer (Q)
|
96% |
27716
35.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4836
178.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5746
212.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4488
165.7 IPS |
|
|
Text Classification (SP)
|
100% |
3249
4.34 KIPS |
|
|
Text Classification (HP)
|
100% |
5671
7.57 KIPS |
|
|
Text Classification (Q)
|
93% |
5606
7.52 KIPS |
|
|
Machine Translation (SP)
|
100% |
3172
54.6 IPS |
|
|
Machine Translation (HP)
|
98% |
6945
120.0 IPS |
|
|
Machine Translation (Q)
|
98% |
6940
119.9 IPS |
