Mac mini (2023)
Geekbench AI Score
4118
Single Precision Score
6748
Half Precision Score
5266
Quantized Score
Geekbench AI 1.2.0 for macOS AArch64
Result Information
| User | mkennedy |
| Upload Date | February 21 2025 05:20 PM |
| Views | 3 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.3.1 (Build 24D70) |
| Model | Mac mini (2023) |
| Model ID | Mac14,12 |
| Motherboard | Mac14,12 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 10 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.48 GHz |
| Cluster 1 | 6 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1381
256.9 IPS |
|
|
Image Classification (HP)
|
100% |
2257
419.8 IPS |
|
|
Image Classification (Q)
|
96% |
1653
308.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1712
27.7 IPS |
|
|
Image Segmentation (HP)
|
100% |
2596
42.1 IPS |
|
|
Image Segmentation (Q)
|
99% |
2914
47.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
12774
14.9 IPS |
|
|
Pose Estimation (HP)
|
100% |
24928
29.1 IPS |
|
|
Pose Estimation (Q)
|
95% |
19014
22.3 IPS |
|
|
Object Detection (SP)
|
100% |
1666
132.2 IPS |
|
|
Object Detection (HP)
|
97% |
2727
217.1 IPS |
|
|
Object Detection (Q)
|
94% |
1987
158.4 IPS |
|
|
Face Detection (SP)
|
100% |
3503
41.6 IPS |
|
|
Face Detection (HP)
|
100% |
5857
69.6 IPS |
|
|
Face Detection (Q)
|
100% |
3360
39.9 IPS |
|
|
Depth Estimation (SP)
|
100% |
6296
48.5 IPS |
|
|
Depth Estimation (HP)
|
98% |
12121
93.7 IPS |
|
|
Depth Estimation (Q)
|
85% |
8149
63.7 IPS |
|
|
Style Transfer (SP)
|
100% |
24783
31.9 IPS |
|
|
Style Transfer (HP)
|
100% |
38900
50.0 IPS |
|
|
Style Transfer (Q)
|
96% |
29981
38.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5073
187.3 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
7038
259.9 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4427
163.5 IPS |
|
|
Text Classification (SP)
|
100% |
2278
3.04 KIPS |
|
|
Text Classification (HP)
|
100% |
4040
5.39 KIPS |
|
|
Text Classification (Q)
|
93% |
4014
5.39 KIPS |
|
|
Machine Translation (SP)
|
100% |
4417
76.1 IPS |
|
|
Machine Translation (HP)
|
98% |
6262
108.2 IPS |
|
|
Machine Translation (Q)
|
98% |
6188
106.9 IPS |
