iPhone 15 Pro Max
Geekbench AI Score
3836
Single Precision Score
26493
Half Precision Score
36489
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| Upload Date | November 11 2025 03:52 PM |
| 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% |
1553
288.8 IPS |
|
|
Image Classification (HP)
|
100% |
10983
2.04 KIPS |
|
|
Image Classification (Q)
|
97% |
15692
2.93 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1532
24.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16476
267.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
21161
343.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7769
9.06 IPS |
|
|
Pose Estimation (HP)
|
100% |
106731
124.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
205938
241.4 IPS |
|
|
Object Detection (SP)
|
100% |
1684
133.6 IPS |
|
|
Object Detection (HP)
|
100% |
13425
1.06 KIPS |
|
|
Object Detection (Q)
|
91% |
17653
1.41 KIPS |
|
|
Face Detection (SP)
|
100% |
3076
36.6 IPS |
|
|
Face Detection (HP)
|
100% |
33918
403.0 IPS |
|
|
Face Detection (Q)
|
100% |
47153
560.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
6930
53.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
78425
604.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
127347
995.7 IPS |
|
|
Style Transfer (SP)
|
100% |
21762
28.0 IPS |
|
|
Style Transfer (HP)
|
100% |
206602
265.6 IPS |
|
|
Style Transfer (Q)
|
96% |
248879
321.2 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4815
177.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35125
1.30 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
61576
2.27 KIPS |
|
|
Text Classification (SP)
|
100% |
3194
4.26 KIPS |
|
|
Text Classification (HP)
|
99% |
5451
7.28 KIPS |
|
|
Text Classification (Q)
|
93% |
5362
7.20 KIPS |
|
|
Machine Translation (SP)
|
100% |
3111
53.6 IPS |
|
|
Machine Translation (HP)
|
100% |
6244
107.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7025
121.4 IPS |
