Mac Studio (2023)
Geekbench AI Score
3181
Single Precision Score
4751
Half Precision Score
3905
Quantized Score
Geekbench AI 1.0.0 for macOS AArch64
Result Information
| User | splifingate |
| Upload Date | August 18 2024 12:48 AM |
| 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 | 3.48 GHz |
| Cluster 1 | 8 Cores |
| Cluster 2 | 4 Cores |
| Memory Information | |
|---|---|
| Size | 64.00 GB |
AI Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (SP)
|
100% |
1486
276.4 IPS |
|
|
Image Classification (HP)
|
100% |
1826
339.5 IPS |
|
|
Image Classification (Q)
|
99% |
1804
336.5 IPS |
|
|
Image Segmentation (SP)
|
100% |
1298
21.0 IPS |
|
|
Image Segmentation (HP)
|
100% |
1304
21.1 IPS |
|
|
Image Segmentation (Q)
|
100% |
1305
21.2 IPS |
|
|
Pose Estimation (SP)
|
100% |
6206
7.24 IPS |
|
|
Pose Estimation (HP)
|
100% |
14804
17.3 IPS |
|
|
Pose Estimation (Q)
|
96% |
12580
14.7 IPS |
|
|
Object Detection (SP)
|
100% |
1578
125.2 IPS |
|
|
Object Detection (HP)
|
97% |
2243
178.6 IPS |
|
|
Object Detection (Q)
|
94% |
1708
136.1 IPS |
|
|
Face Detection (SP)
|
100% |
3042
36.1 IPS |
|
|
Face Detection (HP)
|
100% |
4369
51.9 IPS |
|
|
Face Detection (Q)
|
100% |
2802
33.3 IPS |
|
|
Depth Estimation (SP)
|
100% |
5501
42.4 IPS |
|
|
Depth Estimation (HP)
|
99% |
8644
66.8 IPS |
|
|
Depth Estimation (Q)
|
96% |
4149
32.1 IPS |
|
|
Style Transfer (SP)
|
100% |
16755
21.5 IPS |
|
|
Style Transfer (HP)
|
100% |
26428
34.0 IPS |
|
|
Style Transfer (Q)
|
100% |
26468
34.0 IPS |
|
|
Image Super-Resolution (SP)
|
100% |
3791
140.0 IPS |
|
|
Image Super-Resolution (HP)
|
100% |
4886
180.4 IPS |
|
|
Image Super-Resolution (Q)
|
98% |
3566
132.1 IPS |
|
|
Text Classification (SP)
|
100% |
2257
3.01 KIPS |
|
|
Text Classification (HP)
|
100% |
3385
4.52 KIPS |
|
|
Text Classification (Q)
|
93% |
3345
4.49 KIPS |
|
|
Machine Translation (SP)
|
100% |
2345
40.4 IPS |
|
|
Machine Translation (HP)
|
98% |
4495
77.7 IPS |
|
|
Machine Translation (Q)
|
98% |
4446
76.8 IPS |
