iPhone 15 Pro
Geekbench AI Score
3663
Single Precision Score
26521
Half Precision Score
35705
Quantized Score
Geekbench AI 1.5.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | September 25 2025 02:23 AM |
| Views | 7 |
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 |
| 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% |
1549
288.0 IPS |
|
|
Image Classification (HP)
|
100% |
11360
2.11 KIPS |
|
|
Image Classification (Q)
|
97% |
15147
2.83 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1526
24.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
16515
267.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
21402
346.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
6662
7.77 IPS |
|
|
Pose Estimation (HP)
|
100% |
100804
117.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
201254
235.9 IPS |
|
|
Object Detection (SP)
|
100% |
1639
130.0 IPS |
|
|
Object Detection (HP)
|
100% |
13299
1.05 KIPS |
|
|
Object Detection (Q)
|
91% |
17605
1.41 KIPS |
|
|
Face Detection (SP)
|
100% |
3020
35.9 IPS |
|
|
Face Detection (HP)
|
100% |
34343
408.1 IPS |
|
|
Face Detection (Q)
|
100% |
47459
563.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6451
49.7 IPS |
|
|
Depth Estimation (HP)
|
99% |
78475
604.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
122510
957.8 IPS |
|
|
Style Transfer (SP)
|
100% |
19650
25.3 IPS |
|
|
Style Transfer (HP)
|
100% |
207098
266.2 IPS |
|
|
Style Transfer (Q)
|
96% |
247008
318.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4306
159.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35207
1.30 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55246
2.04 KIPS |
|
|
Text Classification (SP)
|
100% |
3213
4.29 KIPS |
|
|
Text Classification (HP)
|
99% |
5600
7.47 KIPS |
|
|
Text Classification (Q)
|
93% |
5531
7.42 KIPS |
|
|
Machine Translation (SP)
|
100% |
3188
54.9 IPS |
|
|
Machine Translation (HP)
|
100% |
6222
107.2 IPS |
|
|
Machine Translation (Q)
|
98% |
6681
115.5 IPS |
