iPhone17,1
Geekbench AI Score
5604
Single Precision Score
6266
Half Precision Score
5882
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | jayt |
| Upload Date | September 29 2024 12:48 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | ARM |
| 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 | 4.04 GHz |
| Cluster 1 | 2 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 7.49 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3019
561.4 IPS |
|
|
Image Classification (HP)
|
100% |
1828
339.9 IPS |
|
|
Image Classification (Q)
|
97% |
2903
541.8 IPS |
|
|
Image Segmentation (SP)
|
100% |
3457
56.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
4447
72.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
4411
71.5 IPS |
|
|
Pose Estimation (SP)
|
100% |
15580
18.2 IPS |
|
|
Pose Estimation (HP)
|
100% |
16460
19.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
15394
18.0 IPS |
|
|
Object Detection (SP)
|
100% |
3062
242.9 IPS |
|
|
Object Detection (HP)
|
100% |
3584
284.3 IPS |
|
|
Object Detection (Q)
|
91% |
2751
219.8 IPS |
|
|
Face Detection (SP)
|
100% |
7824
93.0 IPS |
|
|
Face Detection (HP)
|
100% |
10721
127.4 IPS |
|
|
Face Detection (Q)
|
100% |
7182
85.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
13290
102.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
14150
109.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
11639
91.0 IPS |
|
|
Style Transfer (SP)
|
100% |
29082
37.4 IPS |
|
|
Style Transfer (HP)
|
100% |
29733
38.2 IPS |
|
|
Style Transfer (Q)
|
96% |
34033
43.9 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
7616
281.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8504
314.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
6502
240.1 IPS |
|
|
Text Classification (SP)
|
100% |
3425
4.57 KIPS |
|
|
Text Classification (HP)
|
100% |
5870
7.83 KIPS |
|
|
Text Classification (Q)
|
93% |
5877
7.89 KIPS |
|
|
Machine Translation (SP)
|
100% |
778
13.4 IPS |
|
|
Machine Translation (HP)
|
100% |
865
14.9 IPS |
|
|
Machine Translation (Q)
|
98% |
841
14.5 IPS |
