iMac (27-inch Retina Mid 2017)
Geekbench AI Score
719
Single Precision Score
92
Half Precision Score
77
Quantized Score
Geekbench AI 1.3.0 for macOS AVX2
Result Information
| Upload Date | May 12 2025 07:04 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Intel Core i5-7600 |
| System Information | |
|---|---|
| Operating System | macOS 15.4.1 (Build 24E263) |
| Model | iMac (27-inch Retina Mid 2017) |
| Model ID | iMac18,3 |
| Motherboard | Apple Inc. Mac-BE088AF8C5EB4FA2 iMac18,3 |
| CPU Information | |
|---|---|
| Name | Intel Core i5-7600 |
| Topology | 1 Processor, 4 Cores |
| Identifier | GenuineIntel Family 6 Model 158 Stepping 9 |
| Base Frequency | 3.50 GHz |
| Cluster 1 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 112.00 GB |
| Transfer Rate | 2667 MT/s |
| Type | DDR4 |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
341
63.4 IPS |
|
|
Image Classification (HP)
|
0
|
||
|
Image Classification (Q)
|
0
|
||
|
Image Segmentation (SP)
|
100% |
371
6.01 IPS |
|
|
Image Segmentation (HP)
|
0
|
||
|
Image Segmentation (Q)
|
0
|
||
|
Pose Estimation (SP)
|
100% |
2201
2.57 IPS |
|
|
Pose Estimation (HP)
|
100% |
523
0.61 IPS |
|
|
Pose Estimation (Q)
|
96% |
483
0.57 IPS |
|
|
Object Detection (SP)
|
100% |
346
27.4 IPS |
|
|
Object Detection (HP)
|
0
|
||
|
Object Detection (Q)
|
0
|
||
|
Face Detection (SP)
|
100% |
864
10.3 IPS |
|
|
Face Detection (HP)
|
100% |
669
7.95 IPS |
|
|
Face Detection (Q)
|
100% |
310
3.69 IPS |
|
|
Depth Estimation (SP)
|
100% |
1010
7.78 IPS |
|
|
Depth Estimation (HP)
|
99% |
824
6.35 IPS |
|
|
Depth Estimation (Q)
|
85% |
576
4.51 IPS |
|
|
Style Transfer (SP)
|
100% |
2857
3.67 IPS |
|
|
Style Transfer (HP)
|
100% |
1941
2.50 IPS |
|
|
Style Transfer (Q)
|
96% |
1626
2.10 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
1198
44.2 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
431
15.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
301
11.1 IPS |
|
|
Text Classification (SP)
|
100% |
437
583.5 IPS |
|
|
Text Classification (HP)
|
100% |
444
592.2 IPS |
|
|
Text Classification (Q)
|
93% |
440
590.5 IPS |
|
|
Machine Translation (SP)
|
100% |
294
5.07 IPS |
|
|
Machine Translation (HP)
|
100% |
447
7.70 IPS |
|
|
Machine Translation (Q)
|
98% |
446
7.70 IPS |
