iPhone17,1
Geekbench ML Score
10281
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for iOS AArch64
Result Information
| Upload Date | November 10 2024 07:40 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| Model | iPhone17,1 |
| Model ID | iPhone17,1 |
| Motherboard | D93AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.03 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 | 7.49 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1593
298.0 IPS |
|
|
Image Classification (F16)
|
100% |
12727
2.38 KIPS |
|
|
Image Classification (I8)
|
99% |
13991
2.62 KIPS |
|
|
Image Segmentation (F32)
|
100% |
1698
28.4 IPS |
|
|
Image Segmentation (F16)
|
100% |
2919
48.8 IPS |
|
|
Image Segmentation (I8)
|
100% |
2943
49.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
15212
18.4 IPS |
|
|
Pose Estimation (F16)
|
100% |
135622
164.2 IPS |
|
|
Pose Estimation (I8)
|
100% |
141041
170.8 IPS |
|
|
Object Detection (F32)
|
100% |
1919
143.2 IPS |
|
|
Object Detection (F16)
|
100% |
6451
481.6 IPS |
|
|
Object Detection (I8)
|
97% |
1406
105.0 IPS |
|
|
Face Detection (F32)
|
100% |
6776
80.6 IPS |
|
|
Face Detection (F16)
|
97% |
21640
257.3 IPS |
|
|
Face Detection (I8)
|
96% |
21954
261.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
13863
107.5 IPS |
|
|
Depth Estimation (F16)
|
100% |
64197
497.8 IPS |
|
|
Depth Estimation (I8)
|
37% |
64953
503.7 IPS |
|
|
Style Transfer (F32)
|
100% |
32658
43.0 IPS |
|
|
Style Transfer (F16)
|
100% |
150051
197.4 IPS |
|
|
Style Transfer (I8)
|
100% |
150244
197.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
6739
240.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
45483
1.62 KIPS |
|
|
Image Super-Resolution (I8)
|
100% |
46262
1.65 KIPS |
|
|
Text Classification (F32)
|
100% |
3168
4.55 KIPS |
|
|
Text Classification (F16)
|
100% |
5423
7.79 KIPS |
|
|
Text Classification (I8)
|
96% |
5437
7.81 KIPS |
|
|
Machine Translation (F32)
|
100% |
600
11.0 IPS |
|
|
Machine Translation (F16)
|
100% |
1667
30.7 IPS |
|
|
Machine Translation (I8)
|
99% |
604
11.1 IPS |
