Mac mini (2023)
Geekbench AI Score
3158
Single Precision Score
4748
Half Precision Score
3945
Quantized Score
Geekbench AI 1.0.0 for macOS AArch64
Result Information
| User | Sprudent3 |
| Upload Date | August 16 2024 12:43 PM |
| Views | 5 |
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 | 3.44 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1476
274.4 IPS |
|
|
Image Classification (HP)
|
100% |
1809
336.4 IPS |
|
|
Image Classification (Q)
|
99% |
1803
336.2 IPS |
|
|
Image Segmentation (SP)
|
100% |
1310
21.2 IPS |
|
|
Image Segmentation (HP)
|
100% |
1298
21.0 IPS |
|
|
Image Segmentation (Q)
|
100% |
1302
21.1 IPS |
|
|
Pose Estimation (SP)
|
100% |
6199
7.23 IPS |
|
|
Pose Estimation (HP)
|
100% |
14796
17.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
12566
14.7 IPS |
|
|
Object Detection (SP)
|
100% |
1590
126.1 IPS |
|
|
Object Detection (HP)
|
97% |
2239
178.2 IPS |
|
|
Object Detection (Q)
|
94% |
1712
136.4 IPS |
|
|
Face Detection (SP)
|
100% |
2928
34.8 IPS |
|
|
Face Detection (HP)
|
100% |
4323
51.4 IPS |
|
|
Face Detection (Q)
|
100% |
2807
33.4 IPS |
|
|
Depth Estimation (SP)
|
100% |
5454
42.0 IPS |
|
|
Depth Estimation (HP)
|
99% |
8567
66.2 IPS |
|
|
Depth Estimation (Q)
|
96% |
4193
32.4 IPS |
|
|
Style Transfer (SP)
|
100% |
16773
21.6 IPS |
|
|
Style Transfer (HP)
|
100% |
26603
34.2 IPS |
|
|
Style Transfer (Q)
|
100% |
26661
34.3 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3790
140.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4753
175.5 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
3561
131.9 IPS |
|
|
Text Classification (SP)
|
100% |
2274
3.03 KIPS |
|
|
Text Classification (HP)
|
100% |
3543
4.73 KIPS |
|
|
Text Classification (Q)
|
93% |
3539
4.75 KIPS |
|
|
Machine Translation (SP)
|
100% |
2248
38.7 IPS |
|
|
Machine Translation (HP)
|
98% |
4518
78.1 IPS |
|
|
Machine Translation (Q)
|
98% |
4577
79.1 IPS |
