Mac mini (Late 2020)
Geekbench ML Score
7169
Core ML Neural Engine Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| User | zoomlenz |
| Upload Date | August 15 2024 05:33 PM |
| Views | 3 |
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 | 3.20 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% |
1840
344.3 IPS |
|
|
Image Classification (F16)
|
100% |
6269
1.17 KIPS |
|
|
Image Classification (I8)
|
99% |
6409
1.20 KIPS |
|
|
Image Segmentation (F32)
|
100% |
846
14.1 IPS |
|
|
Image Segmentation (F16)
|
100% |
3845
64.2 IPS |
|
|
Image Segmentation (I8)
|
100% |
3842
64.2 IPS |
|
|
Pose Estimation (F32)
|
100% |
16325
19.8 IPS |
|
|
Pose Estimation (F16)
|
100% |
62678
75.9 IPS |
|
|
Pose Estimation (I8)
|
100% |
64012
77.5 IPS |
|
|
Object Detection (F32)
|
100% |
1509
112.7 IPS |
|
|
Object Detection (F16)
|
100% |
3917
292.4 IPS |
|
|
Object Detection (I8)
|
97% |
1470
109.8 IPS |
|
|
Face Detection (F32)
|
100% |
5883
69.9 IPS |
|
|
Face Detection (F16)
|
97% |
11520
137.0 IPS |
|
|
Face Detection (I8)
|
96% |
11487
136.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
12336
95.7 IPS |
|
|
Depth Estimation (F16)
|
100% |
41542
322.2 IPS |
|
|
Depth Estimation (I8)
|
37% |
42246
327.6 IPS |
|
|
Style Transfer (F32)
|
100% |
28893
38.0 IPS |
|
|
Style Transfer (F16)
|
100% |
114842
151.1 IPS |
|
|
Style Transfer (I8)
|
100% |
120184
158.1 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
5812
207.5 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
18576
663.4 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
18356
655.5 IPS |
|
|
Text Classification (F32)
|
100% |
1193
1.71 KIPS |
|
|
Text Classification (F16)
|
100% |
2393
3.44 KIPS |
|
|
Text Classification (I8)
|
96% |
2497
3.59 KIPS |
|
|
Machine Translation (F32)
|
100% |
677
12.5 IPS |
|
|
Machine Translation (F16)
|
100% |
2075
38.2 IPS |
|
|
Machine Translation (I8)
|
99% |
658
12.1 IPS |
