iPhone 15 Pro Max
Geekbench AI Score
2770
Single Precision Score
14030
Half Precision Score
16202
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | hass |
| Upload Date | September 05 2024 03:21 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.5.1 |
| 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% |
1449
269.4 IPS |
|
|
Image Classification (HP)
|
100% |
6227
1.16 KIPS |
|
|
Image Classification (Q)
|
99% |
6894
1.29 KIPS |
|
|
Image Segmentation (SP)
|
100% |
827
13.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
5228
84.8 IPS |
|
|
Image Segmentation (Q)
|
100% |
5193
84.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
8042
9.38 IPS |
|
|
Pose Estimation (HP)
|
100% |
87065
101.6 IPS |
|
|
Pose Estimation (Q)
|
94% |
136197
159.8 IPS |
|
|
Object Detection (SP)
|
100% |
1491
118.3 IPS |
|
|
Object Detection (HP)
|
100% |
8160
647.3 IPS |
|
|
Object Detection (Q)
|
93% |
10000
797.9 IPS |
|
|
Face Detection (SP)
|
100% |
2262
26.9 IPS |
|
|
Face Detection (HP)
|
100% |
11242
133.6 IPS |
|
|
Face Detection (Q)
|
100% |
14238
169.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
4651
35.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
42969
331.1 IPS |
|
|
Depth Estimation (Q)
|
97% |
47660
368.5 IPS |
|
|
Style Transfer (SP)
|
100% |
12349
15.9 IPS |
|
|
Style Transfer (HP)
|
100% |
128125
164.7 IPS |
|
|
Style Transfer (Q)
|
100% |
128406
165.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4085
150.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18585
686.3 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
27476
1.02 KIPS |
|
|
Text Classification (SP)
|
100% |
1822
2.43 KIPS |
|
|
Text Classification (HP)
|
71% |
4305
6.19 KIPS |
|
|
Text Classification (Q)
|
69% |
4289
6.29 KIPS |
|
|
Machine Translation (SP)
|
100% |
1916
33.0 IPS |
|
|
Machine Translation (HP)
|
100% |
2581
44.5 IPS |
|
|
Machine Translation (Q)
|
98% |
2490
43.0 IPS |
