iPhone 15 Pro
Geekbench AI Score
3991
Single Precision Score
24351
Half Precision Score
33817
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | Andoni22 |
| Upload Date | May 20 2025 05:51 PM |
| Views | 7 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A17 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.4.1 |
| 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% |
1699
316.0 IPS |
|
|
Image Classification (HP)
|
100% |
11410
2.12 KIPS |
|
|
Image Classification (Q)
|
97% |
15401
2.87 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1605
26.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
15750
255.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
21175
343.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
8211
9.58 IPS |
|
|
Pose Estimation (HP)
|
100% |
108742
126.9 IPS |
|
|
Pose Estimation (Q)
|
95% |
207421
243.1 IPS |
|
|
Object Detection (SP)
|
100% |
1787
141.7 IPS |
|
|
Object Detection (HP)
|
100% |
14050
1.11 KIPS |
|
|
Object Detection (Q)
|
91% |
19359
1.55 KIPS |
|
|
Face Detection (SP)
|
100% |
3180
37.8 IPS |
|
|
Face Detection (HP)
|
100% |
33818
401.8 IPS |
|
|
Face Detection (Q)
|
100% |
51504
612.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
7024
54.1 IPS |
|
|
Depth Estimation (HP)
|
99% |
77860
599.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
129507
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
21544
27.7 IPS |
|
|
Style Transfer (HP)
|
100% |
208299
267.8 IPS |
|
|
Style Transfer (Q)
|
96% |
256694
331.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5000
184.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
33829
1.25 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
59635
2.20 KIPS |
|
|
Text Classification (SP)
|
100% |
3263
4.35 KIPS |
|
|
Text Classification (HP)
|
100% |
2219
2.96 KIPS |
|
|
Text Classification (Q)
|
93% |
1922
2.58 KIPS |
|
|
Machine Translation (SP)
|
100% |
3269
56.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6486
111.7 IPS |
|
|
Machine Translation (Q)
|
98% |
7611
131.5 IPS |
