Mac Studio (2023)
Geekbench AI Score
4149
Single Precision Score
6788
Half Precision Score
5319
Quantized Score
Geekbench AI 1.1.0 for macOS AArch64
Result Information
| User | masm66 |
| Upload Date | November 10 2024 10:40 AM |
| Views | 2 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 15.1 (Build 24B83) |
| Model | Mac Studio (2023) |
| Model ID | Mac14,13 |
| Motherboard | Mac14,13 |
| CPU Information | |
|---|---|
| Name | Apple M2 Max |
| Topology | 1 Processor, 12 Cores |
| Identifier | Apple M2 Max |
| Base Frequency | 3.47 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1391
258.7 IPS |
|
|
Image Classification (HP)
|
100% |
2264
421.1 IPS |
|
|
Image Classification (Q)
|
96% |
1661
310.1 IPS |
|
|
Image Segmentation (SP)
|
100% |
1692
27.4 IPS |
|
|
Image Segmentation (HP)
|
100% |
2643
42.8 IPS |
|
|
Image Segmentation (Q)
|
99% |
2916
47.3 IPS |
|
|
Pose Estimation (SP)
|
100% |
12950
15.1 IPS |
|
|
Pose Estimation (HP)
|
100% |
25008
29.2 IPS |
|
|
Pose Estimation (Q)
|
95% |
19191
22.5 IPS |
|
|
Object Detection (SP)
|
100% |
1694
134.4 IPS |
|
|
Object Detection (HP)
|
97% |
2717
216.3 IPS |
|
|
Object Detection (Q)
|
94% |
2016
160.7 IPS |
|
|
Face Detection (SP)
|
100% |
3565
42.4 IPS |
|
|
Face Detection (HP)
|
100% |
6054
71.9 IPS |
|
|
Face Detection (Q)
|
100% |
3450
41.0 IPS |
|
|
Depth Estimation (SP)
|
100% |
6369
49.1 IPS |
|
|
Depth Estimation (HP)
|
98% |
12275
94.9 IPS |
|
|
Depth Estimation (Q)
|
85% |
8323
65.1 IPS |
|
|
Style Transfer (SP)
|
100% |
24843
31.9 IPS |
|
|
Style Transfer (HP)
|
100% |
38889
50.0 IPS |
|
|
Style Transfer (Q)
|
96% |
30012
38.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
5114
188.9 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
6907
255.0 IPS |
|
|
Image Super-Resolution (Q)
|
99% |
4429
163.6 IPS |
|
|
Text Classification (SP)
|
100% |
2297
3.07 KIPS |
|
|
Text Classification (HP)
|
100% |
4036
5.39 KIPS |
|
|
Text Classification (Q)
|
93% |
3994
5.36 KIPS |
|
|
Machine Translation (SP)
|
100% |
4429
76.3 IPS |
|
|
Machine Translation (HP)
|
98% |
6348
109.7 IPS |
|
|
Machine Translation (Q)
|
98% |
6352
109.8 IPS |
