iPhone 15 Pro Max
Geekbench AI Score
3876
Single Precision Score
6927
Half Precision Score
5653
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | April 16 2025 06:11 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% |
1696
315.3 IPS |
|
|
Image Classification (HP)
|
100% |
2990
556.0 IPS |
|
|
Image Classification (Q)
|
96% |
2035
379.9 IPS |
|
|
Image Segmentation (SP)
|
100% |
1591
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
2334
37.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
3042
49.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
7867
9.18 IPS |
|
|
Pose Estimation (HP)
|
100% |
16337
19.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
14196
16.6 IPS |
|
|
Object Detection (SP)
|
100% |
1776
140.8 IPS |
|
|
Object Detection (HP)
|
97% |
3304
263.0 IPS |
|
|
Object Detection (Q)
|
94% |
2370
188.9 IPS |
|
|
Face Detection (SP)
|
100% |
2951
35.1 IPS |
|
|
Face Detection (HP)
|
100% |
6680
79.4 IPS |
|
|
Face Detection (Q)
|
100% |
3776
44.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6732
51.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
12826
99.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
8987
70.3 IPS |
|
|
Style Transfer (SP)
|
100% |
21198
27.2 IPS |
|
|
Style Transfer (HP)
|
100% |
33375
42.9 IPS |
|
|
Style Transfer (Q)
|
96% |
27591
35.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4730
174.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5893
217.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4397
162.4 IPS |
|
|
Text Classification (SP)
|
100% |
3237
4.32 KIPS |
|
|
Text Classification (HP)
|
100% |
5786
7.72 KIPS |
|
|
Text Classification (Q)
|
93% |
5613
7.53 KIPS |
|
|
Machine Translation (SP)
|
100% |
3153
54.3 IPS |
|
|
Machine Translation (HP)
|
98% |
6932
119.8 IPS |
|
|
Machine Translation (Q)
|
98% |
6929
119.7 IPS |
