iPhone 15 Pro Max
Geekbench AI Score
4008
Single Precision Score
24227
Half Precision Score
32738
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 02:55 AM |
| Views | 1 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.0 |
| 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% |
1710
318.0 IPS |
|
|
Image Classification (HP)
|
100% |
11497
2.14 KIPS |
|
|
Image Classification (Q)
|
97% |
14854
2.77 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1607
26.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
12984
210.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
16004
259.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
8445
9.85 IPS |
|
|
Pose Estimation (HP)
|
100% |
107059
124.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
202508
237.4 IPS |
|
|
Object Detection (SP)
|
100% |
1820
144.3 IPS |
|
|
Object Detection (HP)
|
100% |
13676
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
18963
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3222
38.3 IPS |
|
|
Face Detection (HP)
|
100% |
33641
399.7 IPS |
|
|
Face Detection (Q)
|
100% |
49168
584.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
7194
55.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
78774
606.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
127770
999.0 IPS |
|
|
Style Transfer (SP)
|
100% |
21700
27.9 IPS |
|
|
Style Transfer (HP)
|
100% |
204479
262.9 IPS |
|
|
Style Transfer (Q)
|
96% |
247607
319.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5084
187.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35255
1.30 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
54884
2.03 KIPS |
|
|
Text Classification (SP)
|
100% |
3192
4.26 KIPS |
|
|
Text Classification (HP)
|
100% |
2716
3.62 KIPS |
|
|
Text Classification (Q)
|
93% |
2514
3.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
3103
53.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6144
105.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7219
124.8 IPS |
