iPhone 15 Pro Max
Geekbench AI Score
3889
Single Precision Score
25197
Half Precision Score
35162
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | January 12 2025 04:53 PM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2.1 |
| 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% |
1656
308.0 IPS |
|
|
Image Classification (HP)
|
100% |
11429
2.13 KIPS |
|
|
Image Classification (Q)
|
97% |
14941
2.79 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1588
25.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
15684
254.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
20604
334.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7739
9.03 IPS |
|
|
Pose Estimation (HP)
|
100% |
105682
123.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
203601
238.6 IPS |
|
|
Object Detection (SP)
|
100% |
1776
140.9 IPS |
|
|
Object Detection (HP)
|
100% |
13684
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18734
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3082
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
33595
399.2 IPS |
|
|
Face Detection (Q)
|
100% |
50978
605.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
6967
53.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
78394
604.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
127309
995.4 IPS |
|
|
Style Transfer (SP)
|
100% |
20981
27.0 IPS |
|
|
Style Transfer (HP)
|
100% |
204969
263.5 IPS |
|
|
Style Transfer (Q)
|
96% |
246824
318.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4887
180.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35700
1.32 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57715
2.13 KIPS |
|
|
Text Classification (SP)
|
100% |
3232
4.31 KIPS |
|
|
Text Classification (HP)
|
100% |
3101
4.14 KIPS |
|
|
Text Classification (Q)
|
93% |
3520
4.72 KIPS |
|
|
Machine Translation (SP)
|
100% |
3084
53.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6661
114.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7562
130.7 IPS |
