Mac mini (Late 2020)
Geekbench ML Score
7002
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| User | WrigleyBeard |
| Upload Date | August 17 2024 01:45 AM |
| Views | 2 |
System Information
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| 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 | 3.19 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% |
2058
385.1 IPS |
|
|
Image Classification (F16)
|
100% |
6227
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6284
1.18 KIPS |
|
|
Image Segmentation (F32)
|
100% |
858
14.3 IPS |
|
|
Image Segmentation (F16)
|
100% |
3849
64.3 IPS |
|
|
Image Segmentation (I8)
|
100% |
3846
64.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
16226
19.6 IPS |
|
|
Pose Estimation (F16)
|
100% |
63350
76.7 IPS |
|
|
Pose Estimation (I8)
|
100% |
63134
76.5 IPS |
|
|
Object Detection (F32)
|
100% |
1535
114.6 IPS |
|
|
Object Detection (F16)
|
100% |
3988
297.7 IPS |
|
|
Object Detection (I8)
|
97% |
1526
113.9 IPS |
|
|
Face Detection (F32)
|
100% |
6288
74.8 IPS |
|
|
Face Detection (F16)
|
97% |
11749
139.7 IPS |
|
|
Face Detection (I8)
|
96% |
11726
139.4 IPS |
|
|
Depth Estimation (F32)
|
100% |
12250
95.0 IPS |
|
|
Depth Estimation (F16)
|
100% |
39791
308.6 IPS |
|
|
Depth Estimation (I8)
|
37% |
43845
340.0 IPS |
|
|
Style Transfer (F32)
|
100% |
29130
38.3 IPS |
|
|
Style Transfer (F16)
|
100% |
113855
149.8 IPS |
|
|
Style Transfer (I8)
|
100% |
116928
153.8 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5398
192.8 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
17900
639.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18232
651.1 IPS |
|
|
Text Classification (F32)
|
100% |
541
777.8 IPS |
|
|
Text Classification (F16)
|
100% |
2274
3.27 KIPS |
|
|
Text Classification (I8)
|
96% |
2256
3.24 KIPS |
|
|
Machine Translation (F32)
|
100% |
686
12.6 IPS |
|
|
Machine Translation (F16)
|
100% |
2326
42.8 IPS |
|
|
Machine Translation (I8)
|
99% |
655
12.1 IPS |
