iMac (27-inch Retina Early 2019)
Geekbench AI Score
946
Single Precision Score
115
Half Precision Score
93
Quantized Score
Geekbench AI 1.3.0 for macOS AVX2
Result Information
| User | rbuj |
| Upload Date | April 17 2025 08:25 PM |
| Views | 15 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Intel Core i5-9600K |
| System Information | |
|---|---|
| Operating System | macOS 15.4.1 (Build 24E263) |
| Model | iMac (27-inch Retina Early 2019) |
| Model ID | iMac19,1 |
| Motherboard | Apple Inc. Mac-AA95B1DDAB278B95 iMac19,1 |
| CPU Information | |
|---|---|
| Name | Intel Core i5-9600K |
| Topology | 1 Processor, 6 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 12 |
| Base Frequency | 3.70 GHz |
| Cluster 1 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
| Transfer Rate | 2667 MT/s |
| Type | DDR4 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
482
89.7 IPS |
|
|
Image Classification (HP)
|
0
|
||
|
Image Classification (Q)
|
0
|
||
|
Image Segmentation (SP)
|
100% |
492
7.97 IPS |
|
|
Image Segmentation (HP)
|
0
|
||
|
Image Segmentation (Q)
|
0
|
||
|
Pose Estimation (SP)
|
100% |
2798
3.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
770
0.90 IPS |
|
|
Pose Estimation (Q)
|
96% |
708
0.83 IPS |
|
|
Object Detection (SP)
|
100% |
502
39.8 IPS |
|
|
Object Detection (HP)
|
0
|
||
|
Object Detection (Q)
|
0
|
||
|
Face Detection (SP)
|
100% |
1071
12.7 IPS |
|
|
Face Detection (HP)
|
100% |
850
10.1 IPS |
|
|
Face Detection (Q)
|
100% |
354
4.21 IPS |
|
|
Depth Estimation (SP)
|
100% |
1408
10.8 IPS |
|
|
Depth Estimation (HP)
|
99% |
1154
8.89 IPS |
|
|
Depth Estimation (Q)
|
85% |
735
5.75 IPS |
|
|
Style Transfer (SP)
|
100% |
3837
4.93 IPS |
|
|
Style Transfer (HP)
|
100% |
2948
3.79 IPS |
|
|
Style Transfer (Q)
|
96% |
2346
3.03 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1545
57.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
641
23.7 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
400
14.8 IPS |
|
|
Text Classification (SP)
|
100% |
485
646.7 IPS |
|
|
Text Classification (HP)
|
100% |
486
649.3 IPS |
|
|
Text Classification (Q)
|
93% |
485
651.2 IPS |
|
|
Machine Translation (SP)
|
100% |
399
6.87 IPS |
|
|
Machine Translation (HP)
|
100% |
621
10.7 IPS |
|
|
Machine Translation (Q)
|
98% |
616
10.6 IPS |
