Mac mini (2023)
Geekbench AI Score
6214
Single Precision Score
6923
Half Precision Score
6455
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| User | geekbench_user2983 |
| Upload Date | April 26 2025 02:59 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | GPU |
| Device | Apple M2 |
| System Information | |
|---|---|
| Operating System | macOS 15.4.1 (Build 24E263) |
| Model | Mac mini (2023) |
| Model ID | Mac14,3 |
| Motherboard | Mac14,3 |
| CPU Information | |
|---|---|
| Name | Apple M2 |
| Topology | 1 Processor, 8 Cores |
| Identifier | Apple M2 |
| Base Frequency | 2.90 GHz |
| Cluster 1 | 4 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
3007
559.1 IPS |
|
|
Image Classification (HP)
|
100% |
3048
566.8 IPS |
|
|
Image Classification (Q)
|
96% |
2801
523.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
5122
83.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
4489
72.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
4453
72.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
18229
21.3 IPS |
|
|
Pose Estimation (HP)
|
100% |
19683
23.0 IPS |
|
|
Pose Estimation (Q)
|
96% |
19653
23.0 IPS |
|
|
Object Detection (SP)
|
100% |
2955
234.4 IPS |
|
|
Object Detection (HP)
|
100% |
3064
243.0 IPS |
|
|
Object Detection (Q)
|
92% |
2797
223.3 IPS |
|
|
Face Detection (SP)
|
100% |
7702
91.5 IPS |
|
|
Face Detection (HP)
|
100% |
9345
111.0 IPS |
|
|
Face Detection (Q)
|
100% |
7563
89.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
13317
102.6 IPS |
|
|
Depth Estimation (HP)
|
99% |
14275
110.0 IPS |
|
|
Depth Estimation (Q)
|
85% |
12961
101.3 IPS |
|
|
Style Transfer (SP)
|
100% |
31690
40.7 IPS |
|
|
Style Transfer (HP)
|
100% |
37236
47.9 IPS |
|
|
Style Transfer (Q)
|
96% |
36239
46.8 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
8155
301.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
8710
321.6 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
7444
274.9 IPS |
|
|
Text Classification (SP)
|
100% |
1854
2.48 KIPS |
|
|
Text Classification (HP)
|
100% |
3181
4.25 KIPS |
|
|
Text Classification (Q)
|
93% |
3250
4.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
2106
36.3 IPS |
|
|
Machine Translation (HP)
|
100% |
2230
38.4 IPS |
|
|
Machine Translation (Q)
|
98% |
2132
36.8 IPS |
