iPhone 15 Pro Max
Geekbench AI Score
2635
Single Precision Score
14341
Half Precision Score
15427
Quantized Score
Geekbench AI 1.0.0 for iOS AArch64
Result Information
| User | gundar |
| Upload Date | August 15 2024 08:56 PM |
| Views | 7 |
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% |
1384
257.4 IPS |
|
|
Image Classification (HP)
|
100% |
6276
1.17 KIPS |
|
|
Image Classification (Q)
|
99% |
7029
1.31 KIPS |
|
|
Image Segmentation (SP)
|
100% |
801
13.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
5199
84.3 IPS |
|
|
Image Segmentation (Q)
|
100% |
5243
85.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7431
8.67 IPS |
|
|
Pose Estimation (HP)
|
100% |
88807
103.6 IPS |
|
|
Pose Estimation (Q)
|
94% |
129059
151.4 IPS |
|
|
Object Detection (SP)
|
100% |
1408
111.7 IPS |
|
|
Object Detection (HP)
|
100% |
8211
651.3 IPS |
|
|
Object Detection (Q)
|
93% |
9208
734.7 IPS |
|
|
Face Detection (SP)
|
100% |
2114
25.1 IPS |
|
|
Face Detection (HP)
|
100% |
11031
131.1 IPS |
|
|
Face Detection (Q)
|
100% |
12510
148.7 IPS |
|
|
Depth Estimation (SP)
|
100% |
4485
34.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
42633
328.5 IPS |
|
|
Depth Estimation (Q)
|
97% |
47804
369.6 IPS |
|
|
Style Transfer (SP)
|
100% |
11990
15.4 IPS |
|
|
Style Transfer (HP)
|
100% |
127909
164.4 IPS |
|
|
Style Transfer (Q)
|
100% |
128359
165.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3854
142.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
18378
678.6 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
24982
925.5 IPS |
|
|
Text Classification (SP)
|
100% |
1721
2.30 KIPS |
|
|
Text Classification (HP)
|
71% |
6038
8.68 KIPS |
|
|
Text Classification (Q)
|
69% |
4057
5.95 KIPS |
|
|
Machine Translation (SP)
|
100% |
1851
31.9 IPS |
|
|
Machine Translation (HP)
|
100% |
2317
39.9 IPS |
|
|
Machine Translation (Q)
|
98% |
2242
38.7 IPS |
