iPhone 15 Pro Max
Geekbench AI Score
3827
Single Precision Score
26534
Half Precision Score
35516
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 06 2025 09:37 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.1 |
| 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 | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1568
291.6 IPS |
|
|
Image Classification (HP)
|
100% |
11004
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
14785
2.76 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1528
24.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16390
265.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
21447
347.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
7794
9.09 IPS |
|
|
Pose Estimation (HP)
|
100% |
106148
123.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
203866
238.9 IPS |
|
|
Object Detection (SP)
|
100% |
1686
133.7 IPS |
|
|
Object Detection (HP)
|
100% |
13100
1.04 KIPS |
|
|
Object Detection (Q)
|
91% |
17261
1.38 KIPS |
|
|
Face Detection (SP)
|
100% |
3036
36.1 IPS |
|
|
Face Detection (HP)
|
100% |
34694
412.2 IPS |
|
|
Face Detection (Q)
|
100% |
46256
549.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
6908
53.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
78225
602.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
121766
952.0 IPS |
|
|
Style Transfer (SP)
|
100% |
21455
27.6 IPS |
|
|
Style Transfer (HP)
|
100% |
202893
260.8 IPS |
|
|
Style Transfer (Q)
|
96% |
243640
314.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4759
175.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34613
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57633
2.13 KIPS |
|
|
Text Classification (SP)
|
100% |
3193
4.26 KIPS |
|
|
Text Classification (HP)
|
99% |
5456
7.28 KIPS |
|
|
Text Classification (Q)
|
93% |
5267
7.07 KIPS |
|
|
Machine Translation (SP)
|
100% |
3135
54.0 IPS |
|
|
Machine Translation (HP)
|
100% |
6634
114.3 IPS |
|
|
Machine Translation (Q)
|
98% |
6872
118.7 IPS |
