iPhone 16 Pro
Geekbench AI Score
4416
Single Precision Score
32869
Half Precision Score
45058
Quantized Score
Geekbench AI 1.2.0 for iOS AArch64
Result Information
| User | urix |
| Upload Date | February 21 2025 12:56 PM |
| Views | 13 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 Pro |
| System Information | |
|---|---|
| Operating System | iOS 18.3.1 |
| Model | iPhone 16 Pro |
| Model ID | iPhone17,1 |
| Motherboard | D93AP |
| CPU Information | |
|---|---|
| Name | Apple A18 Pro |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.48 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2038
379.1 IPS |
|
|
Image Classification (HP)
|
100% |
15352
2.85 KIPS |
|
|
Image Classification (Q)
|
97% |
20372
3.80 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1938
31.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
18400
298.3 IPS |
|
|
Image Segmentation (Q)
|
99% |
24163
391.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
8232
9.61 IPS |
|
|
Pose Estimation (HP)
|
100% |
149308
174.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
293144
343.6 IPS |
|
|
Object Detection (SP)
|
100% |
2114
167.7 IPS |
|
|
Object Detection (HP)
|
100% |
16217
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22327
1.78 KIPS |
|
|
Face Detection (SP)
|
100% |
3448
41.0 IPS |
|
|
Face Detection (HP)
|
100% |
41245
490.1 IPS |
|
|
Face Detection (Q)
|
100% |
56560
672.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
7474
57.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
94725
729.8 IPS |
|
|
Depth Estimation (Q)
|
85% |
159452
1.25 KIPS |
|
|
Style Transfer (SP)
|
100% |
22638
29.1 IPS |
|
|
Style Transfer (HP)
|
100% |
244947
314.9 IPS |
|
|
Style Transfer (Q)
|
96% |
301476
389.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5406
199.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
49946
1.84 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
83898
3.10 KIPS |
|
|
Text Classification (SP)
|
100% |
3417
4.56 KIPS |
|
|
Text Classification (HP)
|
100% |
4812
6.42 KIPS |
|
|
Text Classification (Q)
|
93% |
4092
5.49 KIPS |
|
|
Machine Translation (SP)
|
100% |
3816
65.7 IPS |
|
|
Machine Translation (HP)
|
100% |
9358
161.2 IPS |
|
|
Machine Translation (Q)
|
98% |
11470
198.2 IPS |
