iPhone 15 Pro
Geekbench AI Score
3903
Single Precision Score
26680
Half Precision Score
36425
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | September 08 2025 02:30 AM |
| Views | 10 |
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 |
| Model ID | iPhone16,1 |
| Motherboard | D83AP |
| 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 | 7.50 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1682
312.9 IPS |
|
|
Image Classification (HP)
|
100% |
11045
2.05 KIPS |
|
|
Image Classification (Q)
|
97% |
14771
2.76 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1601
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
16673
270.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
21225
344.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
7599
8.87 IPS |
|
|
Pose Estimation (HP)
|
100% |
105243
122.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
204554
239.8 IPS |
|
|
Object Detection (SP)
|
100% |
1761
139.7 IPS |
|
|
Object Detection (HP)
|
100% |
13521
1.07 KIPS |
|
|
Object Detection (Q)
|
91% |
17787
1.42 KIPS |
|
|
Face Detection (SP)
|
100% |
3181
37.8 IPS |
|
|
Face Detection (HP)
|
100% |
36020
428.0 IPS |
|
|
Face Detection (Q)
|
100% |
49927
593.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
6864
52.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
78524
605.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
125512
981.3 IPS |
|
|
Style Transfer (SP)
|
100% |
20623
26.5 IPS |
|
|
Style Transfer (HP)
|
100% |
208297
267.8 IPS |
|
|
Style Transfer (Q)
|
96% |
246014
317.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4753
175.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35104
1.30 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
57832
2.14 KIPS |
|
|
Text Classification (SP)
|
100% |
3252
4.34 KIPS |
|
|
Text Classification (HP)
|
99% |
5454
7.28 KIPS |
|
|
Text Classification (Q)
|
93% |
5493
7.37 KIPS |
|
|
Machine Translation (SP)
|
100% |
3276
56.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6184
106.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7361
127.2 IPS |
