iPhone 15 Pro
Geekbench AI Score
3973
Single Precision Score
24111
Half Precision Score
33229
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | Wierzbi |
| Upload Date | March 08 2025 07:15 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.3.1 |
| 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% |
1696
315.4 IPS |
|
|
Image Classification (HP)
|
100% |
11285
2.10 KIPS |
|
|
Image Classification (Q)
|
97% |
15781
2.95 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1702
27.6 IPS |
|
|
Image Segmentation (HP)
|
100% |
15782
255.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
20940
339.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7975
9.31 IPS |
|
|
Pose Estimation (HP)
|
100% |
106512
124.3 IPS |
|
|
Pose Estimation (Q)
|
95% |
203483
238.5 IPS |
|
|
Object Detection (SP)
|
100% |
1801
142.9 IPS |
|
|
Object Detection (HP)
|
100% |
13798
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
18752
1.50 KIPS |
|
|
Face Detection (SP)
|
100% |
3197
38.0 IPS |
|
|
Face Detection (HP)
|
100% |
34104
405.2 IPS |
|
|
Face Detection (Q)
|
100% |
49851
592.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7058
54.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
78160
602.2 IPS |
|
|
Depth Estimation (Q)
|
85% |
127801
999.2 IPS |
|
|
Style Transfer (SP)
|
100% |
21017
27.0 IPS |
|
|
Style Transfer (HP)
|
100% |
201579
259.1 IPS |
|
|
Style Transfer (Q)
|
96% |
250494
323.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4922
181.8 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34002
1.26 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
58763
2.17 KIPS |
|
|
Text Classification (SP)
|
100% |
3247
4.33 KIPS |
|
|
Text Classification (HP)
|
100% |
2267
3.03 KIPS |
|
|
Text Classification (Q)
|
93% |
1893
2.54 KIPS |
|
|
Machine Translation (SP)
|
100% |
3123
53.8 IPS |
|
|
Machine Translation (HP)
|
100% |
6127
105.5 IPS |
|
|
Machine Translation (Q)
|
98% |
7333
126.7 IPS |
