Mac mini (2024)
Geekbench AI Score
4761
Single Precision Score
7853
Half Precision Score
6327
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | netdevil |
| Upload Date | December 11 2024 05:38 PM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M4 |
| System Information | |
|---|---|
| Operating System | macOS 15.1.1 (Build 24B2091) |
| Model | Mac mini (2024) |
| Model ID | Mac16,10 |
| Motherboard | Mac16,10 |
| CPU Information | |
|---|---|
| Name | Apple M4 |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M4 |
| Base Frequency | 4.41 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 6 Cores |
| Memory Information | |
|---|---|
| Size | 24.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2030
377.5 IPS |
|
|
Image Classification (HP)
|
100% |
3279
609.8 IPS |
|
|
Image Classification (Q)
|
96% |
2301
429.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
2128
34.5 IPS |
|
|
Image Segmentation (HP)
|
100% |
3243
52.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
3635
58.9 IPS |
|
|
Pose Estimation (SP)
|
100% |
10023
11.7 IPS |
|
|
Pose Estimation (HP)
|
100% |
19054
22.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
16580
19.4 IPS |
|
|
Object Detection (SP)
|
100% |
2296
182.1 IPS |
|
|
Object Detection (HP)
|
97% |
3777
300.7 IPS |
|
|
Object Detection (Q)
|
94% |
2734
217.9 IPS |
|
|
Face Detection (SP)
|
100% |
3955
47.0 IPS |
|
|
Face Detection (HP)
|
100% |
7695
91.4 IPS |
|
|
Face Detection (Q)
|
100% |
4467
53.1 IPS |
|
|
Depth Estimation (SP)
|
100% |
8374
64.5 IPS |
|
|
Depth Estimation (HP)
|
97% |
14765
114.1 IPS |
|
|
Depth Estimation (Q)
|
86% |
10332
80.6 IPS |
|
|
Style Transfer (SP)
|
100% |
25471
32.7 IPS |
|
|
Style Transfer (HP)
|
100% |
38702
49.8 IPS |
|
|
Style Transfer (Q)
|
96% |
32097
41.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5782
213.5 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6893
254.5 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4800
177.3 IPS |
|
|
Text Classification (SP)
|
100% |
3159
4.22 KIPS |
|
|
Text Classification (HP)
|
100% |
5627
7.51 KIPS |
|
|
Text Classification (Q)
|
93% |
5570
7.47 KIPS |
|
|
Machine Translation (SP)
|
100% |
3912
67.4 IPS |
|
|
Machine Translation (HP)
|
98% |
6840
118.2 IPS |
|
|
Machine Translation (Q)
|
98% |
6853
118.4 IPS |
