iPhone 15 Pro Max
Geekbench AI Score
3950
Single Precision Score
23847
Half Precision Score
32977
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | MrV |
| Upload Date | November 08 2024 07:22 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.2 |
| 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% |
1703
316.7 IPS |
|
|
Image Classification (HP)
|
100% |
10677
1.99 KIPS |
|
|
Image Classification (Q)
|
97% |
14613
2.73 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1605
26.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
15704
254.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
20871
338.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
8195
9.56 IPS |
|
|
Pose Estimation (HP)
|
100% |
105967
123.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
203772
238.8 IPS |
|
|
Object Detection (SP)
|
100% |
1742
138.2 IPS |
|
|
Object Detection (HP)
|
100% |
13502
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
18264
1.46 KIPS |
|
|
Face Detection (SP)
|
100% |
3195
38.0 IPS |
|
|
Face Detection (HP)
|
100% |
33637
399.7 IPS |
|
|
Face Detection (Q)
|
100% |
50594
601.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
7078
54.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
78122
601.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
125372
980.2 IPS |
|
|
Style Transfer (SP)
|
100% |
21351
27.4 IPS |
|
|
Style Transfer (HP)
|
100% |
202295
260.1 IPS |
|
|
Style Transfer (Q)
|
96% |
246164
317.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5036
186.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33690
1.24 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57625
2.13 KIPS |
|
|
Text Classification (SP)
|
100% |
3156
4.21 KIPS |
|
|
Text Classification (HP)
|
100% |
2320
3.10 KIPS |
|
|
Text Classification (Q)
|
93% |
2024
2.72 KIPS |
|
|
Machine Translation (SP)
|
100% |
3091
53.2 IPS |
|
|
Machine Translation (HP)
|
100% |
5967
102.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7358
127.2 IPS |
