Mac mini (Late 2014)
Geekbench ML Score
393
Core ML GPU Inference Score
Geekbench ML 0.6.0 for macOS AVX2
Result Information
| Upload Date | August 21 2024 04:37 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 | GPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
331
61.9 IPS |
|
|
Image Classification (F16)
|
100% |
305
57.1 IPS |
|
|
Image Classification (I8)
|
99% |
305
57.2 IPS |
|
|
Image Segmentation (F32)
|
100% |
171
2.85 IPS |
|
|
Image Segmentation (F16)
|
100% |
170
2.83 IPS |
|
|
Image Segmentation (I8)
|
100% |
170
2.84 IPS |
|
|
Pose Estimation (F32)
|
100% |
957
1.16 IPS |
|
|
Pose Estimation (F16)
|
100% |
956
1.16 IPS |
|
|
Pose Estimation (I8)
|
100% |
955
1.16 IPS |
|
|
Object Detection (F32)
|
100% |
290
21.7 IPS |
|
|
Object Detection (F16)
|
100% |
287
21.4 IPS |
|
|
Object Detection (I8)
|
97% |
291
21.7 IPS |
|
|
Face Detection (F32)
|
100% |
834
9.92 IPS |
|
|
Face Detection (F16)
|
100% |
805
9.57 IPS |
|
|
Face Detection (I8)
|
99% |
806
9.59 IPS |
|
|
Depth Estimation (F32)
|
100% |
551
4.27 IPS |
|
|
Depth Estimation (F16)
|
100% |
530
4.11 IPS |
|
|
Depth Estimation (I8)
|
37% |
516
4.00 IPS |
|
|
Style Transfer (F32)
|
100% |
939
1.24 IPS |
|
|
Style Transfer (F16)
|
100% |
943
1.24 IPS |
|
|
Style Transfer (I8)
|
100% |
953
1.25 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
263
9.39 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
264
9.43 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
264
9.41 IPS |
|
|
Text Classification (F32)
|
36% |
277
397.9 IPS |
|
|
Text Classification (F16)
|
36% |
283
406.9 IPS |
|
|
Text Classification (I8)
|
36% |
151
217.5 IPS |
|
|
Machine Translation (F32)
|
100% |
264
4.85 IPS |
|
|
Machine Translation (F16)
|
100% |
227
4.18 IPS |
|
|
Machine Translation (I8)
|
99% |
248
4.56 IPS |
