iPhone 15 Pro Max
Geekbench AI Score
2708
Single Precision Score
14137
Half Precision Score
15916
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | macbloke |
| Upload Date | August 29 2024 03:49 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 17.6 |
| 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% |
1443
268.3 IPS |
|
|
Image Classification (HP)
|
100% |
6135
1.14 KIPS |
|
|
Image Classification (Q)
|
99% |
6805
1.27 KIPS |
|
|
Image Segmentation (SP)
|
100% |
815
13.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
5222
84.7 IPS |
|
|
Image Segmentation (Q)
|
100% |
5205
84.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7577
8.84 IPS |
|
|
Pose Estimation (HP)
|
100% |
87833
102.5 IPS |
|
|
Pose Estimation (Q)
|
94% |
130735
153.3 IPS |
|
|
Object Detection (SP)
|
100% |
1461
115.9 IPS |
|
|
Object Detection (HP)
|
100% |
8187
649.4 IPS |
|
|
Object Detection (Q)
|
93% |
10045
801.5 IPS |
|
|
Face Detection (SP)
|
100% |
2191
26.0 IPS |
|
|
Face Detection (HP)
|
100% |
11131
132.3 IPS |
|
|
Face Detection (Q)
|
100% |
12809
152.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
4586
35.3 IPS |
|
|
Depth Estimation (HP)
|
99% |
42624
328.4 IPS |
|
|
Depth Estimation (Q)
|
97% |
47776
369.4 IPS |
|
|
Style Transfer (SP)
|
100% |
12079
15.5 IPS |
|
|
Style Transfer (HP)
|
100% |
127883
164.4 IPS |
|
|
Style Transfer (Q)
|
100% |
128570
165.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3948
145.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18305
675.9 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
25817
956.5 IPS |
|
|
Text Classification (SP)
|
100% |
1792
2.39 KIPS |
|
|
Text Classification (HP)
|
71% |
4943
7.11 KIPS |
|
|
Text Classification (Q)
|
69% |
4467
6.55 KIPS |
|
|
Machine Translation (SP)
|
100% |
1898
32.7 IPS |
|
|
Machine Translation (HP)
|
100% |
2522
43.4 IPS |
|
|
Machine Translation (Q)
|
98% |
2473
42.7 IPS |
