iPhone 15 Pro Max
Geekbench AI Score
3985
Single Precision Score
6879
Half Precision Score
5626
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | VenomF5 |
| Upload Date | September 25 2024 10:31 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1698
315.8 IPS |
|
|
Image Classification (HP)
|
100% |
2935
545.8 IPS |
|
|
Image Classification (Q)
|
96% |
2018
376.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
1614
26.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2412
39.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
3076
49.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
8356
9.75 IPS |
|
|
Pose Estimation (HP)
|
100% |
16862
19.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
14720
17.3 IPS |
|
|
Object Detection (SP)
|
100% |
1786
141.6 IPS |
|
|
Object Detection (HP)
|
97% |
3362
267.7 IPS |
|
|
Object Detection (Q)
|
94% |
2354
187.7 IPS |
|
|
Face Detection (SP)
|
100% |
3226
38.3 IPS |
|
|
Face Detection (HP)
|
100% |
6788
80.7 IPS |
|
|
Face Detection (Q)
|
100% |
3891
46.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
7190
55.4 IPS |
|
|
Depth Estimation (HP)
|
98% |
13535
104.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
9342
73.0 IPS |
|
|
Style Transfer (SP)
|
100% |
21420
27.5 IPS |
|
|
Style Transfer (HP)
|
100% |
32633
42.0 IPS |
|
|
Style Transfer (Q)
|
96% |
27634
35.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5041
186.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5881
217.2 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4474
165.2 IPS |
|
|
Text Classification (SP)
|
100% |
3185
4.25 KIPS |
|
|
Text Classification (HP)
|
100% |
5564
7.43 KIPS |
|
|
Text Classification (Q)
|
93% |
5453
7.32 KIPS |
|
|
Machine Translation (SP)
|
100% |
3098
53.4 IPS |
|
|
Machine Translation (HP)
|
98% |
6033
104.2 IPS |
|
|
Machine Translation (Q)
|
98% |
6032
104.2 IPS |
