Mac mini (Late 2014)
Geekbench ML Score
261
Core ML CPU Inference Score
Geekbench ML 0.6.0 for macOS AVX2
Result Information
| Upload Date | August 21 2024 04:28 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.5 (Build 23F79) |
| Model | Mac mini (Late 2014) |
| Model ID | Macmini7,1 |
| Motherboard | Apple Inc. Mac-35C5E08120C7EEAF Macmini7,1 |
| CPU Information | |
|---|---|
| Name | Intel Core i5-4278U |
| Topology | 1 Processor, 2 Cores, 4 Threads |
| Identifier | GenuineIntel Family 6 Model 69 Stepping 1 |
| Base Frequency | 2.60 GHz |
| Cluster 1 | 2 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 | 3.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 8.00 GB |
| Transfer Rate | 1600 MT/s |
| Type | DDR3 |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
132
24.8 IPS |
|
|
Image Classification (F16)
|
100% |
106
19.9 IPS |
|
|
Image Classification (I8)
|
99% |
110
20.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
96
1.60 IPS |
|
|
Image Segmentation (F16)
|
100% |
90
1.50 IPS |
|
|
Image Segmentation (I8)
|
100% |
87
1.46 IPS |
|
|
Pose Estimation (F32)
|
100% |
948
1.15 IPS |
|
|
Pose Estimation (F16)
|
100% |
645
0.78 IPS |
|
|
Pose Estimation (I8)
|
100% |
648
0.78 IPS |
|
|
Object Detection (F32)
|
100% |
128
9.57 IPS |
|
|
Object Detection (F16)
|
100% |
109
8.13 IPS |
|
|
Object Detection (I8)
|
97% |
127
9.49 IPS |
|
|
Face Detection (F32)
|
100% |
337
4.00 IPS |
|
|
Face Detection (F16)
|
98% |
294
3.50 IPS |
|
|
Face Detection (I8)
|
97% |
295
3.51 IPS |
|
|
Depth Estimation (F32)
|
100% |
556
4.31 IPS |
|
|
Depth Estimation (F16)
|
100% |
429
3.33 IPS |
|
|
Depth Estimation (I8)
|
99% |
430
3.33 IPS |
|
|
Style Transfer (F32)
|
100% |
1012
1.33 IPS |
|
|
Style Transfer (F16)
|
100% |
884
1.16 IPS |
|
|
Style Transfer (I8)
|
100% |
891
1.17 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
588
21.0 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
377
13.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
378
13.5 IPS |
|
|
Text Classification (F32)
|
100% |
177
254.7 IPS |
|
|
Text Classification (F16)
|
100% |
203
292.2 IPS |
|
|
Text Classification (I8)
|
96% |
163
233.9 IPS |
|
|
Machine Translation (F32)
|
100% |
145
2.67 IPS |
|
|
Machine Translation (F16)
|
100% |
169
3.11 IPS |
|
|
Machine Translation (I8)
|
99% |
145
2.66 IPS |
