iPhone 15 Pro Max
Geekbench AI Score
3788
Single Precision Score
26428
Half Precision Score
36022
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | September 19 2025 12:16 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 26.0 |
| 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% |
1590
295.6 IPS |
|
|
Image Classification (HP)
|
100% |
10835
2.02 KIPS |
|
|
Image Classification (Q)
|
97% |
15473
2.89 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1546
25.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
16358
265.2 IPS |
|
|
Image Segmentation (Q)
|
99% |
21284
345.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7460
8.70 IPS |
|
|
Pose Estimation (HP)
|
100% |
106130
123.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
204813
240.1 IPS |
|
|
Object Detection (SP)
|
100% |
1648
130.8 IPS |
|
|
Object Detection (HP)
|
100% |
13794
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18274
1.46 KIPS |
|
|
Face Detection (SP)
|
100% |
3003
35.7 IPS |
|
|
Face Detection (HP)
|
100% |
33704
400.5 IPS |
|
|
Face Detection (Q)
|
100% |
47125
560.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6798
52.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
78446
604.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
122072
954.4 IPS |
|
|
Style Transfer (SP)
|
100% |
20762
26.7 IPS |
|
|
Style Transfer (HP)
|
100% |
206978
266.1 IPS |
|
|
Style Transfer (Q)
|
96% |
249107
321.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4636
171.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34515
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58167
2.15 KIPS |
|
|
Text Classification (SP)
|
100% |
3261
4.35 KIPS |
|
|
Text Classification (HP)
|
99% |
5444
7.27 KIPS |
|
|
Text Classification (Q)
|
93% |
5406
7.26 KIPS |
|
|
Machine Translation (SP)
|
100% |
3147
54.2 IPS |
|
|
Machine Translation (HP)
|
100% |
6230
107.3 IPS |
|
|
Machine Translation (Q)
|
98% |
6624
114.5 IPS |
