iPhone 15 Pro Max
Geekbench AI Score
3889
Single Precision Score
25518
Half Precision Score
35553
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| Upload Date | July 28 2025 11:50 PM |
| Views | 4 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.5 |
| 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% |
1686
313.5 IPS |
|
|
Image Classification (HP)
|
100% |
10741
2.00 KIPS |
|
|
Image Classification (Q)
|
97% |
15809
2.95 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1588
25.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
16376
265.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
21367
346.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7687
8.97 IPS |
|
|
Pose Estimation (HP)
|
100% |
106800
124.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
204528
239.7 IPS |
|
|
Object Detection (SP)
|
100% |
1764
140.0 IPS |
|
|
Object Detection (HP)
|
100% |
13656
1.08 KIPS |
|
|
Object Detection (Q)
|
91% |
18853
1.51 KIPS |
|
|
Face Detection (SP)
|
100% |
3075
36.5 IPS |
|
|
Face Detection (HP)
|
100% |
36620
435.1 IPS |
|
|
Face Detection (Q)
|
100% |
53107
631.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6814
52.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
78629
605.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
127023
993.1 IPS |
|
|
Style Transfer (SP)
|
100% |
20942
26.9 IPS |
|
|
Style Transfer (HP)
|
100% |
205047
263.6 IPS |
|
|
Style Transfer (Q)
|
96% |
253331
326.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4790
176.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33999
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56570
2.09 KIPS |
|
|
Text Classification (SP)
|
100% |
3272
4.37 KIPS |
|
|
Text Classification (HP)
|
100% |
3436
4.59 KIPS |
|
|
Text Classification (Q)
|
93% |
3435
4.61 KIPS |
|
|
Machine Translation (SP)
|
100% |
3177
54.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6618
114.0 IPS |
|
|
Machine Translation (Q)
|
98% |
7461
128.9 IPS |
