iPhone 15 Pro Max
Geekbench AI Score
2723
Single Precision Score
14137
Half Precision Score
16231
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | Gelert |
| Upload Date | August 15 2024 06:24 PM |
| Views | 5 |
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% |
1447
269.2 IPS |
|
|
Image Classification (HP)
|
100% |
6158
1.15 KIPS |
|
|
Image Classification (Q)
|
99% |
7005
1.31 KIPS |
|
|
Image Segmentation (SP)
|
100% |
822
13.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
5222
84.7 IPS |
|
|
Image Segmentation (Q)
|
100% |
5449
88.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
7839
9.15 IPS |
|
|
Pose Estimation (HP)
|
100% |
89493
104.4 IPS |
|
|
Pose Estimation (Q)
|
94% |
135244
158.6 IPS |
|
|
Object Detection (SP)
|
100% |
1469
116.5 IPS |
|
|
Object Detection (HP)
|
100% |
8198
650.3 IPS |
|
|
Object Detection (Q)
|
93% |
9963
794.9 IPS |
|
|
Face Detection (SP)
|
100% |
2205
26.2 IPS |
|
|
Face Detection (HP)
|
100% |
11093
131.8 IPS |
|
|
Face Detection (Q)
|
100% |
13370
158.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
4606
35.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
43193
332.8 IPS |
|
|
Depth Estimation (Q)
|
97% |
47723
369.0 IPS |
|
|
Style Transfer (SP)
|
100% |
12095
15.5 IPS |
|
|
Style Transfer (HP)
|
100% |
128186
164.8 IPS |
|
|
Style Transfer (Q)
|
100% |
128471
165.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4024
148.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18636
688.1 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
27537
1.02 KIPS |
|
|
Text Classification (SP)
|
100% |
1746
2.33 KIPS |
|
|
Text Classification (HP)
|
71% |
4617
6.64 KIPS |
|
|
Text Classification (Q)
|
69% |
4354
6.38 KIPS |
|
|
Machine Translation (SP)
|
100% |
1899
32.7 IPS |
|
|
Machine Translation (HP)
|
100% |
2558
44.1 IPS |
|
|
Machine Translation (Q)
|
98% |
2511
43.4 IPS |
