iPhone 15 Pro Max
Geekbench AI Score
4016
Single Precision Score
24359
Half Precision Score
33856
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 17 2024 03:52 PM |
| 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% |
10938
2.03 KIPS |
|
|
Image Classification (Q)
|
97% |
15480
2.89 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1619
26.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
12821
207.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
16009
259.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
8483
9.90 IPS |
|
|
Pose Estimation (HP)
|
100% |
107169
125.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
202802
237.7 IPS |
|
|
Object Detection (SP)
|
100% |
1820
144.4 IPS |
|
|
Object Detection (HP)
|
100% |
13449
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
19189
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
3220
38.3 IPS |
|
|
Face Detection (HP)
|
100% |
33682
400.2 IPS |
|
|
Face Detection (Q)
|
100% |
49254
585.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
7209
55.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
79203
610.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
128566
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21672
27.9 IPS |
|
|
Style Transfer (HP)
|
100% |
202355
260.1 IPS |
|
|
Style Transfer (Q)
|
96% |
248109
320.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5126
189.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34531
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55617
2.05 KIPS |
|
|
Text Classification (SP)
|
100% |
3190
4.26 KIPS |
|
|
Text Classification (HP)
|
100% |
3169
4.23 KIPS |
|
|
Text Classification (Q)
|
93% |
3173
4.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
3104
53.5 IPS |
|
|
Machine Translation (HP)
|
100% |
6162
106.1 IPS |
|
|
Machine Translation (Q)
|
98% |
7401
127.9 IPS |
