iMac (27-inch Retina Mid 2017)
Geekbench ML Score
2447
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AVX2
Result Information
| User | KipR |
| Upload Date | August 16 2024 09:54 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 13.6.9 (Build 22G830) |
| 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 |
| L1 Instruction Cache | 32.0 KB x 2 |
| L1 Data Cache | 32.0 KB x 2 |
| L2 Cache | 256 KB x 2 |
| L3 Cache | 6.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Transfer Rate | 2400 MT/s |
| Type | DDR4 |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
2047
383.1 IPS |
|
|
Image Classification (F16)
|
100% |
2114
395.6 IPS |
|
|
Image Classification (I8)
|
99% |
2099
392.8 IPS |
|
|
Image Segmentation (F32)
|
100% |
380
6.34 IPS |
|
|
Image Segmentation (F16)
|
100% |
383
6.39 IPS |
|
|
Image Segmentation (I8)
|
100% |
380
6.34 IPS |
|
|
Pose Estimation (F32)
|
100% |
13412
16.2 IPS |
|
|
Pose Estimation (F16)
|
100% |
13979
16.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
13986
16.9 IPS |
|
|
Object Detection (F32)
|
100% |
1535
114.6 IPS |
|
|
Object Detection (F16)
|
100% |
1405
104.9 IPS |
|
|
Object Detection (I8)
|
97% |
1547
115.5 IPS |
|
|
Face Detection (F32)
|
100% |
7083
84.2 IPS |
|
|
Face Detection (F16)
|
97% |
7098
84.4 IPS |
|
|
Face Detection (I8)
|
96% |
6877
81.8 IPS |
|
|
Depth Estimation (F32)
|
100% |
8499
65.9 IPS |
|
|
Depth Estimation (F16)
|
100% |
8852
68.6 IPS |
|
|
Depth Estimation (I8)
|
99% |
8847
68.6 IPS |
|
|
Style Transfer (F32)
|
100% |
26693
35.1 IPS |
|
|
Style Transfer (F16)
|
100% |
27004
35.5 IPS |
|
|
Style Transfer (I8)
|
100% |
27048
35.6 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3630
129.7 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
3353
119.7 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
3361
120.0 IPS |
|
|
Text Classification (F32)
|
100% |
295
424.3 IPS |
|
|
Text Classification (F16)
|
100% |
334
479.8 IPS |
|
|
Text Classification (I8)
|
96% |
335
482.1 IPS |
|
|
Machine Translation (F32)
|
100% |
269
4.95 IPS |
|
|
Machine Translation (F16)
|
100% |
239
4.40 IPS |
|
|
Machine Translation (I8)
|
99% |
268
4.93 IPS |
