iPhone 15 Pro Max
Geekbench AI Score
3769
Single Precision Score
6835
Half Precision Score
5692
Quantized Score
Geekbench AI 1.6.1 for iOS AArch64
Result Information
| User | vchernomya |
| Upload Date | January 13 2026 11:03 AM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.3 |
| 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% |
1553
288.7 IPS |
|
|
Image Classification (HP)
|
100% |
2945
547.7 IPS |
|
|
Image Classification (Q)
|
96% |
2019
377.0 IPS |
|
|
Image Segmentation (SP)
|
100% |
1534
24.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
2359
38.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
2992
48.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7424
8.66 IPS |
|
|
Pose Estimation (HP)
|
100% |
16573
19.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
14466
17.0 IPS |
|
|
Object Detection (SP)
|
100% |
1664
132.0 IPS |
|
|
Object Detection (HP)
|
97% |
3242
258.1 IPS |
|
|
Object Detection (Q)
|
94% |
2350
187.3 IPS |
|
|
Face Detection (SP)
|
100% |
3018
35.9 IPS |
|
|
Face Detection (HP)
|
100% |
6416
76.2 IPS |
|
|
Face Detection (Q)
|
100% |
3804
45.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6824
52.6 IPS |
|
|
Depth Estimation (HP)
|
98% |
12677
98.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
8944
69.9 IPS |
|
|
Style Transfer (SP)
|
100% |
21137
27.2 IPS |
|
|
Style Transfer (HP)
|
100% |
30063
38.6 IPS |
|
|
Style Transfer (Q)
|
96% |
27705
35.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4449
164.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
5832
215.3 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4384
161.9 IPS |
|
|
Text Classification (SP)
|
100% |
3343
4.46 KIPS |
|
|
Text Classification (HP)
|
99% |
5956
7.95 KIPS |
|
|
Text Classification (Q)
|
93% |
5866
7.87 KIPS |
|
|
Machine Translation (SP)
|
100% |
3037
52.3 IPS |
|
|
Machine Translation (HP)
|
98% |
7019
121.3 IPS |
|
|
Machine Translation (Q)
|
98% |
7175
124.0 IPS |
