iPhone 15 Pro Max
Geekbench AI Score
3791
Single Precision Score
25099
Half Precision Score
35081
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | January 03 2025 06:03 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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% |
1663
309.3 IPS |
|
|
Image Classification (HP)
|
100% |
11017
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
15317
2.86 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1573
25.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
15989
259.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
21032
340.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
7299
8.52 IPS |
|
|
Pose Estimation (HP)
|
100% |
101596
118.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
202092
236.9 IPS |
|
|
Object Detection (SP)
|
100% |
1721
136.5 IPS |
|
|
Object Detection (HP)
|
100% |
13892
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
19045
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3097
36.8 IPS |
|
|
Face Detection (HP)
|
100% |
35253
418.9 IPS |
|
|
Face Detection (Q)
|
100% |
51598
613.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
6729
51.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
78640
605.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
126907
992.2 IPS |
|
|
Style Transfer (SP)
|
100% |
19954
25.7 IPS |
|
|
Style Transfer (HP)
|
100% |
202089
259.8 IPS |
|
|
Style Transfer (Q)
|
96% |
246000
317.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4560
168.4 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33458
1.24 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
54512
2.01 KIPS |
|
|
Text Classification (SP)
|
100% |
3199
4.27 KIPS |
|
|
Text Classification (HP)
|
100% |
3408
4.55 KIPS |
|
|
Text Classification (Q)
|
93% |
3334
4.48 KIPS |
|
|
Machine Translation (SP)
|
100% |
3082
53.1 IPS |
|
|
Machine Translation (HP)
|
100% |
6249
107.6 IPS |
|
|
Machine Translation (Q)
|
98% |
7778
134.4 IPS |
