Mac Studio (2023)
Geekbench AI Score
3213
Single Precision Score
4832
Half Precision Score
3999
Quantized Score
Geekbench AI 1.0.0 for macOS AArch64
Result Information
| User | bartjr |
| Upload Date | August 16 2024 04:46 PM |
| Views | 8 |
System Information
| AI Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Apple M2 Max |
| System Information | |
|---|---|
| Operating System | macOS 14.6.1 (Build 23G93) |
| 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 | 3.66 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1485
276.2 IPS |
|
|
Image Classification (HP)
|
100% |
1842
342.6 IPS |
|
|
Image Classification (Q)
|
99% |
1825
340.4 IPS |
|
|
Image Segmentation (SP)
|
100% |
1356
22.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1351
21.9 IPS |
|
|
Image Segmentation (Q)
|
100% |
1346
21.8 IPS |
|
|
Pose Estimation (SP)
|
100% |
6312
7.36 IPS |
|
|
Pose Estimation (HP)
|
100% |
14905
17.4 IPS |
|
|
Pose Estimation (Q)
|
96% |
12648
14.8 IPS |
|
|
Object Detection (SP)
|
100% |
1610
127.7 IPS |
|
|
Object Detection (HP)
|
97% |
2249
179.0 IPS |
|
|
Object Detection (Q)
|
94% |
1729
137.8 IPS |
|
|
Face Detection (SP)
|
100% |
3047
36.2 IPS |
|
|
Face Detection (HP)
|
100% |
4467
53.1 IPS |
|
|
Face Detection (Q)
|
100% |
2966
35.2 IPS |
|
|
Depth Estimation (SP)
|
100% |
5570
42.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
8649
66.8 IPS |
|
|
Depth Estimation (Q)
|
96% |
4241
32.8 IPS |
|
|
Style Transfer (SP)
|
100% |
17079
22.0 IPS |
|
|
Style Transfer (HP)
|
100% |
27029
34.7 IPS |
|
|
Style Transfer (Q)
|
100% |
26985
34.7 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3844
142.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4881
180.2 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
3575
132.4 IPS |
|
|
Text Classification (SP)
|
100% |
2302
3.07 KIPS |
|
|
Text Classification (HP)
|
100% |
3543
4.73 KIPS |
|
|
Text Classification (Q)
|
93% |
3504
4.70 KIPS |
|
|
Machine Translation (SP)
|
100% |
2236
38.5 IPS |
|
|
Machine Translation (HP)
|
98% |
4611
79.7 IPS |
|
|
Machine Translation (Q)
|
98% |
4582
79.2 IPS |
