Mac mini (2023)
Geekbench AI Score
4087
Single Precision Score
6595
Half Precision Score
5272
Quantized Score
Geekbench AI 1.3.0 for macOS AArch64
Result Information
| User | naadams |
| Upload Date | May 14 2025 03:41 AM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 15.5 (Build 24F74) |
| Model | Mac mini (2023) |
| Model ID | Mac14,12 |
| Motherboard | Mac14,12 |
| CPU Information | |
|---|---|
| Name | Apple M2 Pro |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Pro |
| Base Frequency | 3.49 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 16.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1391
258.7 IPS |
|
|
Image Classification (HP)
|
100% |
2245
417.6 IPS |
|
|
Image Classification (Q)
|
96% |
1663
310.6 IPS |
|
|
Image Segmentation (SP)
|
100% |
1616
26.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
2459
39.9 IPS |
|
|
Image Segmentation (Q)
|
99% |
2852
46.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
12431
14.5 IPS |
|
|
Pose Estimation (HP)
|
100% |
25180
29.4 IPS |
|
|
Pose Estimation (Q)
|
95% |
19484
22.8 IPS |
|
|
Object Detection (SP)
|
100% |
1656
131.4 IPS |
|
|
Object Detection (HP)
|
97% |
2620
208.6 IPS |
|
|
Object Detection (Q)
|
94% |
1946
155.1 IPS |
|
|
Face Detection (SP)
|
100% |
3542
42.1 IPS |
|
|
Face Detection (HP)
|
100% |
5546
65.9 IPS |
|
|
Face Detection (Q)
|
100% |
3327
39.5 IPS |
|
|
Depth Estimation (SP)
|
100% |
6086
46.9 IPS |
|
|
Depth Estimation (HP)
|
98% |
11307
87.4 IPS |
|
|
Depth Estimation (Q)
|
85% |
7796
60.9 IPS |
|
|
Style Transfer (SP)
|
100% |
24798
31.9 IPS |
|
|
Style Transfer (HP)
|
100% |
38322
49.3 IPS |
|
|
Style Transfer (Q)
|
96% |
30225
39.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5089
187.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6376
235.4 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4528
167.2 IPS |
|
|
Text Classification (SP)
|
100% |
2380
3.18 KIPS |
|
|
Text Classification (HP)
|
100% |
4155
5.55 KIPS |
|
|
Text Classification (Q)
|
93% |
4176
5.60 KIPS |
|
|
Machine Translation (SP)
|
100% |
4345
74.9 IPS |
|
|
Machine Translation (HP)
|
98% |
6721
116.1 IPS |
|
|
Machine Translation (Q)
|
98% |
6228
107.6 IPS |
