iPhone 15 Pro Max
Geekbench AI Score
4023
Single Precision Score
24448
Half Precision Score
34372
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| Upload Date | September 19 2024 12:32 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% |
1693
314.9 IPS |
|
|
Image Classification (HP)
|
100% |
11647
2.17 KIPS |
|
|
Image Classification (Q)
|
97% |
17264
3.22 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1707
27.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
12894
209.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
16003
259.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
8189
9.55 IPS |
|
|
Pose Estimation (HP)
|
100% |
108002
126.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
202629
237.5 IPS |
|
|
Object Detection (SP)
|
100% |
1807
143.3 IPS |
|
|
Object Detection (HP)
|
100% |
13684
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
19021
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3211
38.2 IPS |
|
|
Face Detection (HP)
|
100% |
33279
395.4 IPS |
|
|
Face Detection (Q)
|
100% |
49113
583.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
7241
55.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
78382
603.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
130090
1.02 KIPS |
|
|
Style Transfer (SP)
|
100% |
21591
27.8 IPS |
|
|
Style Transfer (HP)
|
100% |
204023
262.3 IPS |
|
|
Style Transfer (Q)
|
96% |
249844
322.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5094
188.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34179
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58935
2.18 KIPS |
|
|
Text Classification (SP)
|
100% |
3206
4.28 KIPS |
|
|
Text Classification (HP)
|
100% |
3119
4.16 KIPS |
|
|
Text Classification (Q)
|
93% |
3140
4.21 KIPS |
|
|
Machine Translation (SP)
|
100% |
3168
54.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6059
104.4 IPS |
|
|
Machine Translation (Q)
|
98% |
7319
126.5 IPS |
