iPhone 15 Pro Max
Geekbench AI Score
2668
Single Precision Score
13768
Half Precision Score
17606
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 16 2024 11:30 AM |
| Views | 1 |
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% |
1397
259.8 IPS |
|
|
Image Classification (HP)
|
100% |
6128
1.14 KIPS |
|
|
Image Classification (Q)
|
97% |
7619
1.42 KIPS |
|
|
Image Segmentation (SP)
|
100% |
797
12.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
5227
84.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
9875
160.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7329
8.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
87960
102.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
152023
178.2 IPS |
|
|
Object Detection (SP)
|
100% |
1443
114.5 IPS |
|
|
Object Detection (HP)
|
100% |
8101
642.6 IPS |
|
|
Object Detection (Q)
|
93% |
9880
788.3 IPS |
|
|
Face Detection (SP)
|
100% |
2146
25.5 IPS |
|
|
Face Detection (HP)
|
100% |
11119
132.1 IPS |
|
|
Face Detection (Q)
|
100% |
13254
157.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
4596
35.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
42463
327.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
56753
443.7 IPS |
|
|
Style Transfer (SP)
|
100% |
11880
15.3 IPS |
|
|
Style Transfer (HP)
|
100% |
126666
162.8 IPS |
|
|
Style Transfer (Q)
|
96% |
136825
176.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3924
144.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18295
675.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
25537
943.0 IPS |
|
|
Text Classification (SP)
|
100% |
1812
2.42 KIPS |
|
|
Text Classification (HP)
|
71% |
3929
5.65 KIPS |
|
|
Text Classification (Q)
|
69% |
3891
5.70 KIPS |
|
|
Machine Translation (SP)
|
100% |
1868
32.2 IPS |
|
|
Machine Translation (HP)
|
100% |
2496
43.0 IPS |
|
|
Machine Translation (Q)
|
98% |
2477
42.8 IPS |
