iPhone 16e
Geekbench AI Score
4685
Single Precision Score
35662
Half Precision Score
48642
Quantized Score
Geekbench AI 1.7.0 for iOS AArch64
Result Information
| User | Numair-AIDROOS |
| Upload Date | April 02 2026 06:29 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Apple A18 |
| System Information | |
|---|---|
| Operating System | iOS 26.4 |
| Model | iPhone 16e |
| Model ID | iPhone17,5 |
| Motherboard | V59AP |
| CPU Information | |
|---|---|
| Name | Apple A18 |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.06 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.54 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2000
372.0 IPS |
|
|
Image Classification (HP)
|
100% |
14718
2.74 KIPS |
|
|
Image Classification (Q)
|
97% |
18381
3.43 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1854
30.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
18115
293.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
24274
393.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
7548
8.81 IPS |
|
|
Pose Estimation (HP)
|
100% |
153765
179.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
294577
345.3 IPS |
|
|
Object Detection (SP)
|
100% |
2366
187.7 IPS |
|
|
Object Detection (HP)
|
100% |
15634
1.24 KIPS |
|
|
Object Detection (Q)
|
89% |
21385
1.71 KIPS |
|
|
Face Detection (SP)
|
100% |
3825
45.5 IPS |
|
|
Face Detection (HP)
|
100% |
41291
490.6 IPS |
|
|
Face Detection (Q)
|
100% |
60843
723.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
7593
58.5 IPS |
|
|
Depth Estimation (HP)
|
99% |
94285
726.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
157228
1.23 KIPS |
|
|
Style Transfer (SP)
|
100% |
19404
24.9 IPS |
|
|
Style Transfer (HP)
|
100% |
244607
314.4 IPS |
|
|
Style Transfer (Q)
|
96% |
294487
380.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
4899
180.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
51412
1.90 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
79910
2.95 KIPS |
|
|
Text Classification (SP)
|
99% |
7101
9.48 KIPS |
|
|
Text Classification (HP)
|
99% |
10876
14.5 KIPS |
|
|
Text Classification (Q)
|
92% |
10723
14.4 KIPS |
|
|
Machine Translation (SP)
|
100% |
3928
67.7 IPS |
|
|
Machine Translation (HP)
|
100% |
9749
167.9 IPS |
|
|
Machine Translation (Q)
|
98% |
10929
188.9 IPS |
