iPhone17,2
Geekbench AI Score
4286
Single Precision Score
32226
Half Precision Score
44968
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | mitmul |
| Upload Date | October 12 2024 04:14 PM |
| Views | 5 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.0.1 |
| Model | iPhone17,2 |
| Model ID | iPhone17,2 |
| Motherboard | D94AP |
| CPU Information | |
|---|---|
| Name | ARM |
| Topology | 1 Processor, 6 Cores |
| Identifier | ARM |
| Base Frequency | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.47 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1971
366.6 IPS |
|
|
Image Classification (HP)
|
100% |
15426
2.87 KIPS |
|
|
Image Classification (Q)
|
97% |
20978
3.91 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1864
30.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
14673
237.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
18259
296.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
7990
9.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
147265
171.8 IPS |
|
|
Pose Estimation (Q)
|
95% |
290663
340.7 IPS |
|
|
Object Detection (SP)
|
100% |
2057
163.1 IPS |
|
|
Object Detection (HP)
|
100% |
16252
1.29 KIPS |
|
|
Object Detection (Q)
|
91% |
22601
1.81 KIPS |
|
|
Face Detection (SP)
|
100% |
3342
39.7 IPS |
|
|
Face Detection (HP)
|
100% |
41979
498.8 IPS |
|
|
Face Detection (Q)
|
100% |
56913
676.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
7263
56.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
94887
731.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
161029
1.26 KIPS |
|
|
Style Transfer (SP)
|
100% |
21905
28.2 IPS |
|
|
Style Transfer (HP)
|
100% |
245831
316.0 IPS |
|
|
Style Transfer (Q)
|
96% |
301855
389.5 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5135
189.6 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
49844
1.84 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
84199
3.11 KIPS |
|
|
Text Classification (SP)
|
100% |
3432
4.58 KIPS |
|
|
Text Classification (HP)
|
100% |
4814
6.43 KIPS |
|
|
Text Classification (Q)
|
93% |
4998
6.71 KIPS |
|
|
Machine Translation (SP)
|
100% |
3702
63.8 IPS |
|
|
Machine Translation (HP)
|
100% |
9493
163.5 IPS |
|
|
Machine Translation (Q)
|
98% |
11542
199.5 IPS |
