iPhone 15 Pro Max
Geekbench AI Score
3892
Single Precision Score
24629
Half Precision Score
35996
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| Upload Date | August 26 2025 09:48 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.6.2 |
| 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% |
1690
314.3 IPS |
|
|
Image Classification (HP)
|
100% |
11444
2.13 KIPS |
|
|
Image Classification (Q)
|
97% |
16085
3.00 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1595
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16256
263.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
20855
338.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
8071
9.42 IPS |
|
|
Pose Estimation (HP)
|
100% |
107865
125.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
206743
242.3 IPS |
|
|
Object Detection (SP)
|
100% |
1794
142.3 IPS |
|
|
Object Detection (HP)
|
100% |
13503
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
19984
1.60 KIPS |
|
|
Face Detection (SP)
|
100% |
3127
37.2 IPS |
|
|
Face Detection (HP)
|
100% |
25598
304.2 IPS |
|
|
Face Detection (Q)
|
100% |
51529
612.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6685
51.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
76206
587.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
126874
992.0 IPS |
|
|
Style Transfer (SP)
|
100% |
22172
28.5 IPS |
|
|
Style Transfer (HP)
|
100% |
207026
266.1 IPS |
|
|
Style Transfer (Q)
|
96% |
255054
329.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4307
159.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34840
1.29 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58751
2.17 KIPS |
|
|
Text Classification (SP)
|
100% |
3271
4.37 KIPS |
|
|
Text Classification (HP)
|
100% |
3348
4.47 KIPS |
|
|
Text Classification (Q)
|
93% |
3507
4.71 KIPS |
|
|
Machine Translation (SP)
|
100% |
3136
54.0 IPS |
|
|
Machine Translation (HP)
|
100% |
6435
110.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7672
132.6 IPS |
