iPhone 15 Pro Max
Geekbench AI Score
3677
Single Precision Score
5431
Half Precision Score
4525
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | mattmcq |
| Upload Date | August 16 2024 12:23 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| 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% |
1738
323.3 IPS |
|
|
Image Classification (HP)
|
100% |
2186
406.5 IPS |
|
|
Image Classification (Q)
|
99% |
2188
408.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1414
22.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
1338
21.7 IPS |
|
|
Image Segmentation (Q)
|
100% |
1331
21.6 IPS |
|
|
Pose Estimation (SP)
|
100% |
7669
8.95 IPS |
|
|
Pose Estimation (HP)
|
100% |
15917
18.6 IPS |
|
|
Pose Estimation (Q)
|
96% |
13731
16.1 IPS |
|
|
Object Detection (SP)
|
100% |
1725
136.8 IPS |
|
|
Object Detection (HP)
|
97% |
2571
204.7 IPS |
|
|
Object Detection (Q)
|
94% |
1968
156.8 IPS |
|
|
Face Detection (SP)
|
100% |
2858
34.0 IPS |
|
|
Face Detection (HP)
|
100% |
4898
58.2 IPS |
|
|
Face Detection (Q)
|
100% |
3135
37.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6242
48.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
9548
73.8 IPS |
|
|
Depth Estimation (Q)
|
96% |
4925
38.1 IPS |
|
|
Style Transfer (SP)
|
100% |
19875
25.5 IPS |
|
|
Style Transfer (HP)
|
100% |
30186
38.8 IPS |
|
|
Style Transfer (Q)
|
100% |
29878
38.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4622
170.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5718
211.1 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
4319
160.0 IPS |
|
|
Text Classification (SP)
|
100% |
3127
4.17 KIPS |
|
|
Text Classification (HP)
|
100% |
5189
6.93 KIPS |
|
|
Text Classification (Q)
|
93% |
5157
6.92 KIPS |
|
|
Machine Translation (SP)
|
100% |
2718
46.8 IPS |
|
|
Machine Translation (HP)
|
98% |
4461
77.1 IPS |
|
|
Machine Translation (Q)
|
98% |
4456
77.0 IPS |
