iPhone 15 Pro
Geekbench AI Score
3876
Single Precision Score
23836
Half Precision Score
34215
Quantized Score
Geekbench AI 1.4.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | July 21 2025 08:22 PM |
| 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 |
| 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% |
1658
308.4 IPS |
|
|
Image Classification (HP)
|
100% |
8855
1.65 KIPS |
|
|
Image Classification (Q)
|
97% |
12503
2.33 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1592
25.8 IPS |
|
|
Image Segmentation (HP)
|
100% |
16324
264.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
21560
349.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7369
8.60 IPS |
|
|
Pose Estimation (HP)
|
100% |
100050
116.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
191964
225.0 IPS |
|
|
Object Detection (SP)
|
100% |
1756
139.3 IPS |
|
|
Object Detection (HP)
|
100% |
10024
795.1 IPS |
|
|
Object Detection (Q)
|
91% |
17060
1.36 KIPS |
|
|
Face Detection (SP)
|
100% |
3192
37.9 IPS |
|
|
Face Detection (HP)
|
100% |
34535
410.3 IPS |
|
|
Face Detection (Q)
|
100% |
46860
556.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
6820
52.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
59267
456.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
92754
725.2 IPS |
|
|
Style Transfer (SP)
|
100% |
20878
26.8 IPS |
|
|
Style Transfer (HP)
|
100% |
194597
250.2 IPS |
|
|
Style Transfer (Q)
|
96% |
226777
292.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4692
173.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
24835
917.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
50000
1.85 KIPS |
|
|
Text Classification (SP)
|
100% |
3242
4.33 KIPS |
|
|
Text Classification (HP)
|
99% |
5498
7.34 KIPS |
|
|
Text Classification (Q)
|
93% |
5307
7.12 KIPS |
|
|
Machine Translation (SP)
|
100% |
3245
55.9 IPS |
|
|
Machine Translation (HP)
|
100% |
7511
129.4 IPS |
|
|
Machine Translation (Q)
|
98% |
9523
164.6 IPS |
