iPhone17,1
Geekbench AI Score
4590
Single Precision Score
33098
Half Precision Score
45772
Quantized Score
Geekbench AI 1.1.0 for iOS AArch64
Result Information
| User | VampirSilphy |
| Upload Date | November 22 2024 07:28 PM |
| Views | 10 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | ARM |
| System Information | |
|---|---|
| Operating System | iOS 18.1.1 |
| 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% |
2023
376.2 IPS |
|
|
Image Classification (HP)
|
100% |
15262
2.84 KIPS |
|
|
Image Classification (Q)
|
97% |
20637
3.85 KIPS |
|
|
Image Segmentation (SP)
|
100% |
1966
31.9 IPS |
|
|
Image Segmentation (HP)
|
100% |
18300
296.7 IPS |
|
|
Image Segmentation (Q)
|
99% |
24069
390.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
9027
10.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
153059
178.6 IPS |
|
|
Pose Estimation (Q)
|
95% |
294254
344.9 IPS |
|
|
Object Detection (SP)
|
100% |
2151
170.6 IPS |
|
|
Object Detection (HP)
|
100% |
16376
1.30 KIPS |
|
|
Object Detection (Q)
|
91% |
22634
1.81 KIPS |
|
|
Face Detection (SP)
|
100% |
3697
43.9 IPS |
|
|
Face Detection (HP)
|
100% |
41291
490.6 IPS |
|
|
Face Detection (Q)
|
100% |
57413
682.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
7914
61.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
95416
735.1 IPS |
|
|
Depth Estimation (Q)
|
85% |
160572
1.26 KIPS |
|
|
Style Transfer (SP)
|
100% |
24548
31.6 IPS |
|
|
Style Transfer (HP)
|
100% |
244387
314.2 IPS |
|
|
Style Transfer (Q)
|
96% |
301526
389.1 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5754
212.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
50045
1.85 KIPS |
|
|
Image Super-Resolution (Q)
|
99% |
85115
3.14 KIPS |
|
|
Text Classification (SP)
|
100% |
3426
4.57 KIPS |
|
|
Text Classification (HP)
|
100% |
4873
6.50 KIPS |
|
|
Text Classification (Q)
|
93% |
4547
6.10 KIPS |
|
|
Machine Translation (SP)
|
100% |
3800
65.5 IPS |
|
|
Machine Translation (HP)
|
100% |
9600
165.4 IPS |
|
|
Machine Translation (Q)
|
98% |
11342
196.0 IPS |
