iPhone 15 Pro Max
Geekbench AI Score
4033
Single Precision Score
24977
Half Precision Score
33630
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | January 07 2025 04:23 AM |
| 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% |
1710
318.0 IPS |
|
|
Image Classification (HP)
|
100% |
11744
2.18 KIPS |
|
|
Image Classification (Q)
|
97% |
15935
2.97 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1612
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
15750
255.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
20883
338.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8628
10.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
107014
124.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
204091
239.2 IPS |
|
|
Object Detection (SP)
|
100% |
1832
145.3 IPS |
|
|
Object Detection (HP)
|
100% |
13949
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
18931
1.51 KIPS |
|
|
Face Detection (SP)
|
100% |
3198
38.0 IPS |
|
|
Face Detection (HP)
|
100% |
33892
402.7 IPS |
|
|
Face Detection (Q)
|
100% |
49608
589.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
7220
55.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
78335
603.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
127561
997.3 IPS |
|
|
Style Transfer (SP)
|
100% |
22161
28.5 IPS |
|
|
Style Transfer (HP)
|
100% |
203136
261.1 IPS |
|
|
Style Transfer (Q)
|
96% |
245064
316.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5128
189.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34253
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57740
2.13 KIPS |
|
|
Text Classification (SP)
|
100% |
3198
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
3005
4.01 KIPS |
|
|
Text Classification (Q)
|
93% |
2094
2.81 KIPS |
|
|
Machine Translation (SP)
|
100% |
3116
53.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6166
106.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7678
132.7 IPS |
