iPhone 15 Pro Max
Geekbench AI Score
3828
Single Precision Score
24954
Half Precision Score
34759
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | December 22 2024 02:09 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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% |
1703
316.8 IPS |
|
|
Image Classification (HP)
|
100% |
11480
2.13 KIPS |
|
|
Image Classification (Q)
|
97% |
15259
2.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1585
25.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
15682
254.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
20878
338.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7499
8.75 IPS |
|
|
Pose Estimation (HP)
|
100% |
103645
120.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
201777
236.5 IPS |
|
|
Object Detection (SP)
|
100% |
1753
139.1 IPS |
|
|
Object Detection (HP)
|
100% |
13616
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
18922
1.51 KIPS |
|
|
Face Detection (SP)
|
100% |
3078
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
35465
421.4 IPS |
|
|
Face Detection (Q)
|
100% |
51115
607.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
6665
51.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
78253
602.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
127097
993.7 IPS |
|
|
Style Transfer (SP)
|
100% |
20033
25.8 IPS |
|
|
Style Transfer (HP)
|
100% |
201208
258.7 IPS |
|
|
Style Transfer (Q)
|
96% |
247063
318.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4694
173.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33770
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
54897
2.03 KIPS |
|
|
Text Classification (SP)
|
100% |
3190
4.26 KIPS |
|
|
Text Classification (HP)
|
100% |
3162
4.22 KIPS |
|
|
Text Classification (Q)
|
93% |
3269
4.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
3100
53.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6182
106.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7349
127.0 IPS |
