iPhone17,2
Geekbench AI Score
4466
Single Precision Score
32348
Half Precision Score
44191
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | alexxha |
| Upload Date | September 21 2024 08:53 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.1 |
| 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% |
2001
372.2 IPS |
|
|
Image Classification (HP)
|
100% |
15161
2.82 KIPS |
|
|
Image Classification (Q)
|
97% |
20436
3.81 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1954
31.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
14652
237.5 IPS |
|
|
Image Segmentation (Q)
|
99% |
18325
297.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
8745
10.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
153717
179.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
291533
341.7 IPS |
|
|
Object Detection (SP)
|
100% |
2116
167.8 IPS |
|
|
Object Detection (HP)
|
100% |
16405
1.30 KIPS |
|
|
Object Detection (Q)
|
91% |
22293
1.78 KIPS |
|
|
Face Detection (SP)
|
100% |
3529
41.9 IPS |
|
|
Face Detection (HP)
|
100% |
40820
485.0 IPS |
|
|
Face Detection (Q)
|
100% |
54650
649.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
7690
59.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
94962
731.6 IPS |
|
|
Depth Estimation (Q)
|
85% |
160835
1.26 KIPS |
|
|
Style Transfer (SP)
|
100% |
23387
30.1 IPS |
|
|
Style Transfer (HP)
|
100% |
245839
316.0 IPS |
|
|
Style Transfer (Q)
|
96% |
302773
390.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5443
201.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
49656
1.83 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
84902
3.14 KIPS |
|
|
Text Classification (SP)
|
100% |
3407
4.55 KIPS |
|
|
Text Classification (HP)
|
100% |
4952
6.61 KIPS |
|
|
Text Classification (Q)
|
93% |
4533
6.08 KIPS |
|
|
Machine Translation (SP)
|
100% |
3710
63.9 IPS |
|
|
Machine Translation (HP)
|
100% |
9560
164.7 IPS |
|
|
Machine Translation (Q)
|
98% |
11394
196.9 IPS |
