Mac Studio (2023)
Geekbench AI Score
3202
Single Precision Score
4749
Half Precision Score
3958
Quantized Score
Geekbench AI 1.0.0 for macOS AArch64
Result Information
| User | radoslab |
| Upload Date | August 17 2024 10:37 AM |
| Views | 3 |
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 | 3.47 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1484
276.1 IPS |
|
|
Image Classification (HP)
|
100% |
1831
340.6 IPS |
|
|
Image Classification (Q)
|
99% |
1821
339.7 IPS |
|
|
Image Segmentation (SP)
|
100% |
1297
21.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1293
21.0 IPS |
|
|
Image Segmentation (Q)
|
100% |
1298
21.0 IPS |
|
|
Pose Estimation (SP)
|
100% |
6273
7.32 IPS |
|
|
Pose Estimation (HP)
|
100% |
14845
17.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
12619
14.8 IPS |
|
|
Object Detection (SP)
|
100% |
1607
127.5 IPS |
|
|
Object Detection (HP)
|
97% |
2241
178.4 IPS |
|
|
Object Detection (Q)
|
94% |
1726
137.6 IPS |
|
|
Face Detection (SP)
|
100% |
3062
36.4 IPS |
|
|
Face Detection (HP)
|
100% |
4380
52.0 IPS |
|
|
Face Detection (Q)
|
100% |
2916
34.6 IPS |
|
|
Depth Estimation (SP)
|
100% |
5562
42.9 IPS |
|
|
Depth Estimation (HP)
|
99% |
8669
67.0 IPS |
|
|
Depth Estimation (Q)
|
96% |
4260
33.0 IPS |
|
|
Style Transfer (SP)
|
100% |
16960
21.8 IPS |
|
|
Style Transfer (HP)
|
100% |
26940
34.6 IPS |
|
|
Style Transfer (Q)
|
100% |
26950
34.6 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3837
141.7 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4787
176.8 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
3582
132.7 IPS |
|
|
Text Classification (SP)
|
100% |
2265
3.02 KIPS |
|
|
Text Classification (HP)
|
100% |
3337
4.45 KIPS |
|
|
Text Classification (Q)
|
93% |
3359
4.51 KIPS |
|
|
Machine Translation (SP)
|
100% |
2328
40.1 IPS |
|
|
Machine Translation (HP)
|
98% |
4540
78.4 IPS |
|
|
Machine Translation (Q)
|
98% |
4552
78.7 IPS |
