Mac mini (2023)
Geekbench AI Score
3168
Single Precision Score
4785
Half Precision Score
3958
Quantized Score
Geekbench AI 1.0.0 for macOS AArch64
Result Information
| User | Sprudent3 |
| Upload Date | August 22 2024 07:30 PM |
| Views | 6 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Pro |
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| 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 | 3.48 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1488
276.8 IPS |
|
|
Image Classification (HP)
|
100% |
1829
340.0 IPS |
|
|
Image Classification (Q)
|
99% |
1829
341.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1302
21.1 IPS |
|
|
Image Segmentation (HP)
|
100% |
1303
21.1 IPS |
|
|
Image Segmentation (Q)
|
100% |
1302
21.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6224
7.26 IPS |
|
|
Pose Estimation (HP)
|
100% |
14818
17.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
12599
14.8 IPS |
|
|
Object Detection (SP)
|
100% |
1591
126.2 IPS |
|
|
Object Detection (HP)
|
97% |
2231
177.6 IPS |
|
|
Object Detection (Q)
|
94% |
1724
137.4 IPS |
|
|
Face Detection (SP)
|
100% |
2992
35.5 IPS |
|
|
Face Detection (HP)
|
100% |
4415
52.5 IPS |
|
|
Face Detection (Q)
|
100% |
2843
33.8 IPS |
|
|
Depth Estimation (SP)
|
100% |
5476
42.2 IPS |
|
|
Depth Estimation (HP)
|
99% |
8615
66.6 IPS |
|
|
Depth Estimation (Q)
|
96% |
4038
31.2 IPS |
|
|
Style Transfer (SP)
|
100% |
16774
21.6 IPS |
|
|
Style Transfer (HP)
|
100% |
26534
34.1 IPS |
|
|
Style Transfer (Q)
|
100% |
26722
34.4 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3794
140.1 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4776
176.4 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
3621
134.2 IPS |
|
|
Text Classification (SP)
|
100% |
2303
3.07 KIPS |
|
|
Text Classification (HP)
|
100% |
3657
4.88 KIPS |
|
|
Text Classification (Q)
|
93% |
3613
4.85 KIPS |
|
|
Machine Translation (SP)
|
100% |
2217
38.2 IPS |
|
|
Machine Translation (HP)
|
98% |
4538
78.4 IPS |
|
|
Machine Translation (Q)
|
98% |
4550
78.6 IPS |
