Mac mini (Late 2020)
Geekbench ML Score
6839
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| User | Pom2Ter |
| Upload Date | March 28 2024 03:54 PM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.4.1 (Build 23E224) |
| Model | Mac mini (Late 2020) |
| Model ID | Macmini9,1 |
| Motherboard | Macmini9,1 |
| CPU Information | |
|---|---|
| Name | Apple M1 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M1 |
| Base Frequency | 3.20 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | Neural Engine |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1768
330.8 IPS |
|
|
Image Classification (F16)
|
100% |
6142
1.15 KIPS |
|
|
Image Classification (I8)
|
99% |
6338
1.19 KIPS |
|
|
Image Segmentation (F32)
|
100% |
852
14.2 IPS |
|
|
Image Segmentation (F16)
|
100% |
3779
63.1 IPS |
|
|
Image Segmentation (I8)
|
100% |
3888
64.9 IPS |
|
|
Pose Estimation (F32)
|
100% |
16392
19.9 IPS |
|
|
Pose Estimation (F16)
|
100% |
63298
76.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
64180
77.7 IPS |
|
|
Object Detection (F32)
|
100% |
1536
114.6 IPS |
|
|
Object Detection (F16)
|
100% |
3845
287.1 IPS |
|
|
Object Detection (I8)
|
97% |
1478
110.3 IPS |
|
|
Face Detection (F32)
|
100% |
6074
72.2 IPS |
|
|
Face Detection (F16)
|
97% |
11718
139.3 IPS |
|
|
Face Detection (I8)
|
96% |
11606
138.0 IPS |
|
|
Depth Estimation (F32)
|
100% |
12197
94.6 IPS |
|
|
Depth Estimation (F16)
|
100% |
40104
311.0 IPS |
|
|
Depth Estimation (I8)
|
37% |
41028
318.2 IPS |
|
|
Style Transfer (F32)
|
100% |
28774
37.8 IPS |
|
|
Style Transfer (F16)
|
100% |
114932
151.2 IPS |
|
|
Style Transfer (I8)
|
100% |
120359
158.3 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5025
179.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18173
649.0 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18139
647.8 IPS |
|
|
Text Classification (F32)
|
100% |
435
625.6 IPS |
|
|
Text Classification (F16)
|
100% |
2232
3.21 KIPS |
|
|
Text Classification (I8)
|
96% |
2263
3.25 KIPS |
|
|
Machine Translation (F32)
|
100% |
682
12.6 IPS |
|
|
Machine Translation (F16)
|
100% |
2079
38.3 IPS |
|
|
Machine Translation (I8)
|
99% |
660
12.2 IPS |
