iPhone 15 Pro Max
Geekbench AI Score
3766
Single Precision Score
26729
Half Precision Score
36501
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 26 2025 05:28 AM |
| Views | 1 |
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% |
1572
292.4 IPS |
|
|
Image Classification (HP)
|
100% |
11018
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
15625
2.92 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1554
25.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
16475
267.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
21560
349.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7353
8.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
106504
124.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
205756
241.2 IPS |
|
|
Object Detection (SP)
|
100% |
1651
130.9 IPS |
|
|
Object Detection (HP)
|
100% |
13853
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
18205
1.45 KIPS |
|
|
Face Detection (SP)
|
100% |
3016
35.8 IPS |
|
|
Face Detection (HP)
|
100% |
34762
413.1 IPS |
|
|
Face Detection (Q)
|
100% |
51195
608.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6689
51.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
78308
603.3 IPS |
|
|
Depth Estimation (Q)
|
85% |
125428
980.7 IPS |
|
|
Style Transfer (SP)
|
100% |
20658
26.6 IPS |
|
|
Style Transfer (HP)
|
100% |
205758
264.5 IPS |
|
|
Style Transfer (Q)
|
96% |
247091
318.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4595
169.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34791
1.28 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55163
2.04 KIPS |
|
|
Text Classification (SP)
|
100% |
3246
4.33 KIPS |
|
|
Text Classification (HP)
|
99% |
5513
7.36 KIPS |
|
|
Text Classification (Q)
|
93% |
5451
7.32 KIPS |
|
|
Machine Translation (SP)
|
100% |
3119
53.7 IPS |
|
|
Machine Translation (HP)
|
100% |
6471
111.5 IPS |
|
|
Machine Translation (Q)
|
98% |
6974
120.5 IPS |
