Mac Studio (2023)
Geekbench ML Score
3477
Core ML CPU Inference Score
Geekbench ML 0.6.0 for macOS AArch64
Result Information
| User | radoslab |
| Upload Date | August 17 2024 10:33 AM |
| Views | 3 |
System Information
| 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 |
| L1 Instruction Cache | 128 KB x 1 |
| L1 Data Cache | 64.0 KB x 1 |
| L2 Cache | 4.00 MB x 1 |
| Memory Information | |
|---|---|
| Size | 32.00 GB |
| Inference Information | |
|---|---|
| Framework | Core ML |
| Backend | CPU |
| Device | Default |
Inference Performance
| Workload | Accuracy | Score | |
|---|---|---|---|
|
Image Classification (F32)
|
100% |
1448
271.1 IPS |
|
|
Image Classification (F16)
|
100% |
1807
338.1 IPS |
|
|
Image Classification (I8)
|
99% |
1815
339.6 IPS |
|
|
Image Segmentation (F32)
|
100% |
890
14.9 IPS |
|
|
Image Segmentation (F16)
|
100% |
891
14.9 IPS |
|
|
Image Segmentation (I8)
|
100% |
881
14.7 IPS |
|
|
Pose Estimation (F32)
|
100% |
6040
7.31 IPS |
|
|
Pose Estimation (F16)
|
100% |
14397
17.4 IPS |
|
|
Pose Estimation (I8)
|
100% |
14234
17.2 IPS |
|
|
Object Detection (F32)
|
100% |
1470
109.8 IPS |
|
|
Object Detection (F16)
|
100% |
1984
148.1 IPS |
|
|
Object Detection (I8)
|
97% |
1465
109.4 IPS |
|
|
Face Detection (F32)
|
100% |
3006
35.7 IPS |
|
|
Face Detection (F16)
|
97% |
4258
50.6 IPS |
|
|
Face Detection (I8)
|
97% |
4338
51.6 IPS |
|
|
Depth Estimation (F32)
|
100% |
5464
42.4 IPS |
|
|
Depth Estimation (F16)
|
100% |
8557
66.4 IPS |
|
|
Depth Estimation (I8)
|
99% |
8472
65.7 IPS |
|
|
Style Transfer (F32)
|
100% |
16282
21.4 IPS |
|
|
Style Transfer (F16)
|
100% |
26277
34.6 IPS |
|
|
Style Transfer (I8)
|
100% |
26191
34.5 IPS |
|
|
Image Super-Resolution (F32)
|
100% |
3950
141.1 IPS |
|
|
Image Super-Resolution (F16)
|
100% |
4966
177.3 IPS |
|
|
Image Super-Resolution (I8)
|
100% |
4920
175.7 IPS |
|
|
Text Classification (F32)
|
100% |
2100
3.02 KIPS |
|
|
Text Classification (F16)
|
100% |
3084
4.43 KIPS |
|
|
Text Classification (I8)
|
96% |
3054
4.39 KIPS |
|
|
Machine Translation (F32)
|
100% |
1165
21.4 IPS |
|
|
Machine Translation (F16)
|
100% |
1551
28.5 IPS |
|
|
Machine Translation (I8)
|
99% |
1162
21.4 IPS |
