iPhone 15 Pro
Geekbench AI Score
3938
Single Precision Score
23528
Half Precision Score
30715
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | September 16 2024 10:34 AM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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 | 7.51 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1663
309.3 IPS |
|
|
Image Classification (HP)
|
100% |
11361
2.11 KIPS |
|
|
Image Classification (Q)
|
97% |
15087
2.82 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1625
26.3 IPS |
|
|
Image Segmentation (HP)
|
100% |
12950
209.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
16155
261.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
7581
8.85 IPS |
|
|
Pose Estimation (HP)
|
100% |
106055
123.7 IPS |
|
|
Pose Estimation (Q)
|
95% |
204496
239.7 IPS |
|
|
Object Detection (SP)
|
100% |
1811
143.6 IPS |
|
|
Object Detection (HP)
|
100% |
13851
1.10 KIPS |
|
|
Object Detection (Q)
|
91% |
19138
1.53 KIPS |
|
|
Face Detection (SP)
|
100% |
3242
38.5 IPS |
|
|
Face Detection (HP)
|
100% |
33674
400.1 IPS |
|
|
Face Detection (Q)
|
100% |
49308
585.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
7133
55.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
78427
604.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
128444
1.00 KIPS |
|
|
Style Transfer (SP)
|
100% |
21073
27.1 IPS |
|
|
Style Transfer (HP)
|
100% |
138772
178.4 IPS |
|
|
Style Transfer (Q)
|
96% |
165750
213.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4948
182.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
35918
1.33 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
55387
2.05 KIPS |
|
|
Text Classification (SP)
|
100% |
3182
4.25 KIPS |
|
|
Text Classification (HP)
|
100% |
2867
3.83 KIPS |
|
|
Text Classification (Q)
|
93% |
1850
2.48 KIPS |
|
|
Machine Translation (SP)
|
100% |
3156
54.4 IPS |
|
|
Machine Translation (HP)
|
100% |
6374
109.8 IPS |
|
|
Machine Translation (Q)
|
98% |
7285
125.9 IPS |
