iPhone 15 Pro
Geekbench AI Score
3891
Single Precision Score
23271
Half Precision Score
31391
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | M91 |
| Upload Date | September 15 2024 10:33 AM |
| Views | 2 |
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% |
1671
310.8 IPS |
|
|
Image Classification (HP)
|
100% |
10743
2.00 KIPS |
|
|
Image Classification (Q)
|
97% |
14909
2.78 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1599
25.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
12946
209.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
16004
259.4 IPS |
|
|
Pose Estimation (SP)
|
100% |
7363
8.59 IPS |
|
|
Pose Estimation (HP)
|
100% |
104166
121.5 IPS |
|
|
Pose Estimation (Q)
|
95% |
203486
238.5 IPS |
|
|
Object Detection (SP)
|
100% |
1779
141.1 IPS |
|
|
Object Detection (HP)
|
100% |
13702
1.09 KIPS |
|
|
Object Detection (Q)
|
91% |
19049
1.52 KIPS |
|
|
Face Detection (SP)
|
100% |
3245
38.6 IPS |
|
|
Face Detection (HP)
|
100% |
33639
399.7 IPS |
|
|
Face Detection (Q)
|
100% |
49357
586.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6993
53.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
78724
606.5 IPS |
|
|
Depth Estimation (Q)
|
85% |
129243
1.01 KIPS |
|
|
Style Transfer (SP)
|
100% |
20528
26.4 IPS |
|
|
Style Transfer (HP)
|
100% |
138207
177.7 IPS |
|
|
Style Transfer (Q)
|
96% |
165435
213.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4867
179.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
34374
1.27 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
56792
2.10 KIPS |
|
|
Text Classification (SP)
|
100% |
3183
4.25 KIPS |
|
|
Text Classification (HP)
|
100% |
3052
4.07 KIPS |
|
|
Text Classification (Q)
|
93% |
2261
3.04 KIPS |
|
|
Machine Translation (SP)
|
100% |
3151
54.3 IPS |
|
|
Machine Translation (HP)
|
100% |
6111
105.3 IPS |
|
|
Machine Translation (Q)
|
98% |
7414
128.1 IPS |
