iPhone 15 Pro Max
Geekbench AI Score
2718
Single Precision Score
13950
Half Precision Score
15850
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| Upload Date | August 21 2024 08:30 AM |
| Views | 24 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.6.1 |
| 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 | 7.44 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1440
267.9 IPS |
|
|
Image Classification (HP)
|
100% |
6216
1.16 KIPS |
|
|
Image Classification (Q)
|
99% |
6812
1.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
810
13.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
5211
84.5 IPS |
|
|
Image Segmentation (Q)
|
100% |
5205
84.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7587
8.85 IPS |
|
|
Pose Estimation (HP)
|
100% |
87817
102.5 IPS |
|
|
Pose Estimation (Q)
|
94% |
138444
162.4 IPS |
|
|
Object Detection (SP)
|
100% |
1463
116.0 IPS |
|
|
Object Detection (HP)
|
100% |
8145
646.0 IPS |
|
|
Object Detection (Q)
|
93% |
10049
801.8 IPS |
|
|
Face Detection (SP)
|
100% |
2241
26.6 IPS |
|
|
Face Detection (HP)
|
100% |
11097
131.9 IPS |
|
|
Face Detection (Q)
|
100% |
12762
151.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
4657
35.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
42304
325.9 IPS |
|
|
Depth Estimation (Q)
|
97% |
47554
367.7 IPS |
|
|
Style Transfer (SP)
|
100% |
12193
15.7 IPS |
|
|
Style Transfer (HP)
|
100% |
127888
164.4 IPS |
|
|
Style Transfer (Q)
|
100% |
128222
164.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3915
144.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18231
673.2 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
25822
956.7 IPS |
|
|
Text Classification (SP)
|
100% |
1799
2.40 KIPS |
|
|
Text Classification (HP)
|
71% |
4312
6.20 KIPS |
|
|
Text Classification (Q)
|
69% |
4243
6.22 KIPS |
|
|
Machine Translation (SP)
|
100% |
1898
32.7 IPS |
|
|
Machine Translation (HP)
|
100% |
2554
44.0 IPS |
|
|
Machine Translation (Q)
|
98% |
2380
41.1 IPS |
