Mac mini (2024)
Geekbench AI Score
4770
Single Precision Score
7840
Half Precision Score
6313
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | trolich |
| Upload Date | December 11 2024 08:34 PM |
| Views | 19 |
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 | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
2046
380.5 IPS |
|
|
Image Classification (HP)
|
100% |
3297
613.1 IPS |
|
|
Image Classification (Q)
|
96% |
2311
431.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
2110
34.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
3182
51.6 IPS |
|
|
Image Segmentation (Q)
|
99% |
3623
58.7 IPS |
|
|
Pose Estimation (SP)
|
100% |
10081
11.8 IPS |
|
|
Pose Estimation (HP)
|
100% |
19053
22.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
16600
19.5 IPS |
|
|
Object Detection (SP)
|
100% |
2300
182.4 IPS |
|
|
Object Detection (HP)
|
97% |
3824
304.4 IPS |
|
|
Object Detection (Q)
|
94% |
2757
219.7 IPS |
|
|
Face Detection (SP)
|
100% |
3979
47.3 IPS |
|
|
Face Detection (HP)
|
100% |
7670
91.1 IPS |
|
|
Face Detection (Q)
|
100% |
4441
52.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
8384
64.6 IPS |
|
|
Depth Estimation (HP)
|
97% |
14837
114.7 IPS |
|
|
Depth Estimation (Q)
|
86% |
10353
80.8 IPS |
|
|
Style Transfer (SP)
|
100% |
25404
32.7 IPS |
|
|
Style Transfer (HP)
|
100% |
38531
49.5 IPS |
|
|
Style Transfer (Q)
|
96% |
31981
41.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5793
213.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6852
253.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4779
176.5 IPS |
|
|
Text Classification (SP)
|
100% |
3160
4.22 KIPS |
|
|
Text Classification (HP)
|
100% |
5446
7.27 KIPS |
|
|
Text Classification (Q)
|
93% |
5326
7.15 KIPS |
|
|
Machine Translation (SP)
|
100% |
3927
67.6 IPS |
|
|
Machine Translation (HP)
|
98% |
7017
121.2 IPS |
|
|
Machine Translation (Q)
|
98% |
7011
121.2 IPS |
