iPhone 14
Geekbench ML Score
5146
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | December 06 2024 01:50 AM |
| Views | 1 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 16.5.1 |
| Model | iPhone 14 |
| Model ID | iPhone14,7 |
| Motherboard | D27AP |
| CPU Information | |
|---|---|
| Name | Apple A15 Bionic |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 3.23 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 5.56 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
734
137.3 IPS |
|
|
Image Classification (F16)
|
100% |
5671
1.06 KIPS |
|
|
Image Classification (I8)
|
99% |
5520
1.03 KIPS |
|
|
Image Segmentation (F32)
|
100% |
566
9.46 IPS |
|
|
Image Segmentation (F16)
|
100% |
2957
49.4 IPS |
|
|
Image Segmentation (I8)
|
100% |
3064
51.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
11187
13.5 IPS |
|
|
Pose Estimation (F16)
|
100% |
76833
93.0 IPS |
|
|
Pose Estimation (I8)
|
100% |
75975
92.0 IPS |
|
|
Object Detection (F32)
|
100% |
1377
102.8 IPS |
|
|
Object Detection (F16)
|
100% |
3418
255.1 IPS |
|
|
Object Detection (I8)
|
97% |
1278
95.4 IPS |
|
|
Face Detection (F32)
|
100% |
4262
50.7 IPS |
|
|
Face Detection (F16)
|
97% |
11151
132.6 IPS |
|
|
Face Detection (I8)
|
96% |
11078
131.7 IPS |
|
|
Depth Estimation (F32)
|
100% |
8687
67.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
25685
199.2 IPS |
|
|
Depth Estimation (I8)
|
99% |
24420
189.4 IPS |
|
|
Style Transfer (F32)
|
100% |
18899
24.9 IPS |
|
|
Style Transfer (F16)
|
100% |
90531
119.1 IPS |
|
|
Style Transfer (I8)
|
100% |
90345
118.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
2894
103.4 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
11757
419.9 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
12222
436.5 IPS |
|
|
Text Classification (F32)
|
100% |
423
607.8 IPS |
|
|
Text Classification (F16)
|
100% |
840
1.21 KIPS |
|
|
Text Classification (I8)
|
96% |
862
1.24 KIPS |
|
|
Machine Translation (F32)
|
100% |
833
15.3 IPS |
|
|
Machine Translation (F16)
|
100% |
1247
22.9 IPS |
|
|
Machine Translation (I8)
|
99% |
818
15.1 IPS |
