iPhone 15 Pro Max
Geekbench AI Score
3931
Single Precision Score
25568
Half Precision Score
34546
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| Upload Date | May 07 2025 04:39 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4.1 |
| 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 | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1699
315.9 IPS |
|
|
Image Classification (HP)
|
100% |
10783
2.01 KIPS |
|
|
Image Classification (Q)
|
97% |
15550
2.90 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1589
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16594
269.0 IPS |
|
|
Image Segmentation (Q)
|
99% |
21326
345.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7821
9.13 IPS |
|
|
Pose Estimation (HP)
|
100% |
106257
124.0 IPS |
|
|
Pose Estimation (Q)
|
95% |
205401
240.7 IPS |
|
|
Object Detection (SP)
|
100% |
1776
140.9 IPS |
|
|
Object Detection (HP)
|
100% |
14031
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
19502
1.56 KIPS |
|
|
Face Detection (SP)
|
100% |
3127
37.2 IPS |
|
|
Face Detection (HP)
|
100% |
36536
434.1 IPS |
|
|
Face Detection (Q)
|
100% |
52520
624.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6978
53.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
78232
602.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
128212
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
21304
27.4 IPS |
|
|
Style Transfer (HP)
|
100% |
207839
267.2 IPS |
|
|
Style Transfer (Q)
|
96% |
255719
330.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4900
180.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33786
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57167
2.11 KIPS |
|
|
Text Classification (SP)
|
100% |
3249
4.34 KIPS |
|
|
Text Classification (HP)
|
100% |
3297
4.40 KIPS |
|
|
Text Classification (Q)
|
93% |
2462
3.30 KIPS |
|
|
Machine Translation (SP)
|
100% |
3177
54.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6765
116.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7520
130.0 IPS |
